From c431bea4519e4f2dc6e8fbdfa228d779685aa030 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 22 Apr 2024 16:23:24 -0700 Subject: [PATCH 001/117] automated solvation shell extraction workflow --- .gitignore | 1 + electrolytes/run_extraction.sh | 19 +++ electrolytes/solvation_shell_extract.py | 181 ++++++++++++++++++++++++ electrolytes/solvation_shell_utils.py | 77 ++++++++++ 4 files changed, 278 insertions(+) create mode 100755 electrolytes/run_extraction.sh create mode 100644 electrolytes/solvation_shell_extract.py create mode 100644 electrolytes/solvation_shell_utils.py diff --git a/.gitignore b/.gitignore index b61ebc3..264f1a8 100644 --- a/.gitignore +++ b/.gitignore @@ -4,6 +4,7 @@ checkpoints results logs *.traj +*.pdb experimental # Byte-compiled / optimized / DLL files diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh new file mode 100755 index 0000000..ee69d52 --- /dev/null +++ b/electrolytes/run_extraction.sh @@ -0,0 +1,19 @@ +#!/bin/bash +#TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? + +# Run these scripts from om-data/electrolytes +python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ + --save_dir '/home/sanjeevr/om-data/electrolytes/' \ + --system_name 'NaCl_Water' \ + --solute_atom 'NA0' \ + --min_coord 2 \ + --max_coord 5 \ + --top_n 20 + +python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ + --save_dir '/home/sanjeevr/om-data/electrolytes/' \ + --system_name 'NaCl_Water' \ + --solute_atom 'CL0' \ + --min_coord 2 \ + --max_coord 5 \ + --top_n 20 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py new file mode 100644 index 0000000..5e1ea5a --- /dev/null +++ b/electrolytes/solvation_shell_extract.py @@ -0,0 +1,181 @@ +import os +import logging +import argparse +import numpy as np +from tqdm import tqdm +from collections import defaultdict +import matplotlib.pyplot as plt +import MDAnalysis as mda +import nglview as nv +from solvation_analysis.solute import Solute +from solvation_analysis._column_names import * +from pymatgen.core.structure import Molecule +from solvation_shell_utils import filter_by_rmsd + +logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) + + +def extract_solvation_shells( + pdb_file_path: str, + save_dir: str, + system_name: str, + solute_atom: str, + min_coord: int, + max_coord: int, + top_n: int, +): + """ + Given a MD trajectory in a PDB file, perform a solvation analysis + on the specified solute to extract the first solvation shell. For each coordination number in the specified range, + extract and save the top_n most diverse snapshots based on a RMSD criterion. + + Args: + pdb_file_path: Path to the PDB file containing the MD trajectory + save_dir: Directory in which to save extracted solvation shells + system_name: Name of the system - used for naming the save directory + solute_atom: Name (in the PDB file) of the solute atom type (e.g NA0) with which to perform the solvation analysis + min_coord: Minimum coordination number to consider + max_coord: Maximum coordination number to consider + top_n: Number of snapshots to extract per coordination number. + """ + + # Create save directory + os.makedirs(os.path.join(save_dir, system_name, solute_atom), exist_ok=True) + + # Initialize MDA Universe + universe = mda.Universe(pdb_file_path) + + # Add PBC box + with open(pdb_file_path) as file: + dimension_lines = file.readlines()[1] + a = float(dimension_lines.split()[1]) + b = float(dimension_lines.split()[2]) + c = float(dimension_lines.split()[3]) + universe.dimensions = [a, b, c, 90, 90, 90] + + lattices = np.array([a, b, c])[None][None] + + # Choose solute atom + solu = universe.select_atoms(f"name {solute_atom}") + + logging.info("Translating atoms to solute center of mass") + for ts in tqdm(universe.trajectory): + ts.dimensions = universe.dimensions + solu_center = solu.center_of_mass(wrap=True) + dim = ts.triclinic_dimensions + box_center = np.sum(dim, axis=0) / 2 + universe.atoms.translate(box_center - solu_center) + + universe.atoms.unwrap() + + solvent = universe.atoms - solu + + solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name=solute_atom) + + # Identify the cutoff for the first solvation shell, based on the MD trajectory + logging.info("Running solvation analysis") + solv_anal.run() + + # Plot the RDF + solv_anal.plot_solvation_radius("solute", "solvent") + plt.savefig(os.path.join(save_dir, system_name, solute_atom, "solvation_rdf.png")) + + # There's probably a much faster way to do this + # But for now, we're prototyping, so slow is okay + shells = dict() + for j in solv_anal.speciation.speciation_fraction["solvent"]: + shells[j] = solv_anal.speciation.get_shells({"solvent": j}) + + # Now let's try getting the most diverse structures for each particular coordination number + # This is also a bit slow, particularly for the more common and/or larger solvent shells + for c in range(min_coord, max_coord + 1): + logging.info(f"Processing shells with coordination number {c}") + os.makedirs( + os.path.join(save_dir, system_name, solute_atom, f"coord={c}"), + exist_ok=True, + ) + shell_species = list() + shell_positions = list() + for index, _ in tqdm(shells[c].iterrows()): + ts = universe.trajectory[index[0]] + universe.atoms.unwrap() + shell = solv_anal.solvation_data.xs( + (index[0], index[1]), level=(FRAME, SOLUTE_IX) + ) + shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) + shell = shell.copy() + if len(shell.atoms.elements) > len(shell_species): + shell_species = shell.atoms.elements + + shell_positions.append(shell.atoms.positions) + + by_num_atoms = defaultdict(list) + for sps in shell_positions: + by_num_atoms[len(sps)].append(sps) + + selections_by_num_atoms = { + k: filter_by_rmsd(v, top_n) for k, v in by_num_atoms.items() + } + + for k, v in selections_by_num_atoms.items(): + for ii, positions in enumerate(v): + if positions.shape[0] == shell_species.shape[0]: + # Wrap positions + displacements = ( + positions[:, np.newaxis, :] - positions[np.newaxis, :, :] + ) + idx = np.where(displacements > lattices / 2)[0] + dim = np.where(displacements > lattices / 2)[2] + if idx.shape[0] > 0: + positions[idx, dim] -= lattices[0, 0, dim] + # Save shell as xyz file + mol = Molecule(shell_species, positions, charge=-1) + mol.to( + os.path.join( + save_dir, + system_name, + solute_atom, + f"coord={c}", + f"size{k}_selection{ii}.xyz", + ), + "xyz", + ) + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("--pdb_file_path", type=str, help="PDB trajectory file path") + parser.add_argument("--save_dir", type=str, help="Path to save xyz files") + parser.add_argument( + "--system_name", type=str, help="Name of system used for directory naming" + ) + parser.add_argument( + "--solute_atom", + type=str, + help="Which solute atom to extract solvation shells for", + ) + parser.add_argument( + "--min_coord", type=int, help="Minimum shell coordination number to extract" + ) + parser.add_argument( + "--max_coord", type=int, help="Maximum shell coordination number to extract" + ) + parser.add_argument( + "--top_n", + type=int, + default=20, + help="Number of most diverse shells to extract per coordination number", + ) + + args = parser.parse_args() + + extract_solvation_shells( + args.pdb_file_path, + args.save_dir, + args.system_name, + args.solute_atom, + args.min_coord, + args.max_coord, + args.top_n, + ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py new file mode 100644 index 0000000..74d39e4 --- /dev/null +++ b/electrolytes/solvation_shell_utils.py @@ -0,0 +1,77 @@ +import copy +import itertools +import numpy as np + + +def rmsd(a, b): + """ + Compute the root mean squared distance between two sets of coordinates + Args: + a: numpy array of positions, shape [N_atoms, 3] + b: numpy array of positions, shape [N_atoms, 3] + """ + return np.sqrt(np.mean(np.linalg.norm(b - a, axis=1))) + + +def filter_by_rmsd(coords, n=20): + """ + From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of RMSD" + + Because of the way that IonSolvR data is organized, should be able to just directly calculate rmsd on numpy coordinate arrays + + Args: + coords: list of np.ndarrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! + Note that this latter requirement shouldn't be a problem, specifically when dealing with IonSolvR data. + n: number of most diverse coordinates to return + """ + + states = {0} + min_rmsds = np.array([rmsd(coords[0], coords[i]) for i in range(len(coords))]) + for i in range(n - 1): + best = np.argmax(min_rmsds) + min_rmsds = np.minimum( + min_rmsds, + np.array([rmsd(coords[best], coords[i]) for i in range(len(coords))]), + ) + states.add(best) + + return [coords[i] for i in states] + + +def reorient(box_dimensions, coords, nsolute, solute_natoms, solvent_natoms): + """ + This function is not currently used in the pdb-file based solvation analysis + """ + + transforms = [ + np.array(x) * box_dimensions + for x in itertools.product([0, -1, 1], [0, -1, 1], [0, -1, 1]) + ] + + cog_solu = np.mean(coords[:solute_natoms], axis=0) + + n_solvents = int((len(coords) - nsolute * solute_natoms) / solvent_natoms) + + final_box = np.zeros(coords.shape) + final_box[: nsolute * solute_natoms] = coords[: nsolute * solute_natoms] + + for i in range(n_solvents): + min_dist = np.inf + best_coords = np.zeros((solvent_natoms, 3)) + + start_index = nsolute * solute_natoms + i * solvent_natoms + coords_i = coords[start_index : start_index + solvent_natoms] + assert len(coords_i) == solvent_natoms + + for transform in transforms: + coords_copy = copy.deepcopy(coords_i) + for i in range(solvent_natoms): + coords_copy[i] += transform + + cog_solv = np.mean(coords_copy, axis=0) + dist = np.linalg.norm(cog_solv - cog_solu) + if dist < min_dist: + min_dist = dist + best_coords = coords_copy + final_box[start_index : start_index + solvent_natoms] = best_coords + return final_box From 9c75284d7ba2e1034cd3b22563967d674adff1a0 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 14 May 2024 23:27:42 -0700 Subject: [PATCH 002/117] begin addressing Daniel comments --- electrolytes/run_extraction.sh | 4 ++-- electrolytes/solvation_shell_extract.py | 20 +++++++++++--------- electrolytes/solvation_shell_utils.py | 12 ++++++------ 3 files changed, 19 insertions(+), 17 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index ee69d52..1ccc233 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -3,7 +3,7 @@ # Run these scripts from om-data/electrolytes python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ - --save_dir '/home/sanjeevr/om-data/electrolytes/' \ + --save_dir 'results' \ --system_name 'NaCl_Water' \ --solute_atom 'NA0' \ --min_coord 2 \ @@ -11,7 +11,7 @@ python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electr --top_n 20 python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ - --save_dir '/home/sanjeevr/om-data/electrolytes/' \ + --save_dir 'results' \ --system_name 'NaCl_Water' \ --solute_atom 'CL0' \ --min_coord 2 \ diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 5e1ea5a..7678ed4 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -94,8 +94,8 @@ def extract_solvation_shells( os.path.join(save_dir, system_name, solute_atom, f"coord={c}"), exist_ok=True, ) - shell_species = list() - shell_positions = list() + shell_species = [] + shell_positions = [] for index, _ in tqdm(shells[c].iterrows()): ts = universe.trajectory[index[0]] universe.atoms.unwrap() @@ -113,30 +113,32 @@ def extract_solvation_shells( for sps in shell_positions: by_num_atoms[len(sps)].append(sps) + # filter by number of atoms per shell selections_by_num_atoms = { k: filter_by_rmsd(v, top_n) for k, v in by_num_atoms.items() } - for k, v in selections_by_num_atoms.items(): - for ii, positions in enumerate(v): - if positions.shape[0] == shell_species.shape[0]: + for shell_size, shells in selections_by_num_atoms.items(): #loop over sizes + import pdb; pdb.set_trace() + for idx, shell_pos in enumerate(shells): + if shell_pos.shape[0] == shell_species.shape[0]: # Wrap positions displacements = ( - positions[:, np.newaxis, :] - positions[np.newaxis, :, :] + shell_pos[:, np.newaxis, :] - shell_pos[np.newaxis, :, :] ) idx = np.where(displacements > lattices / 2)[0] dim = np.where(displacements > lattices / 2)[2] if idx.shape[0] > 0: - positions[idx, dim] -= lattices[0, 0, dim] + shell_pos[idx, dim] -= lattices[0, 0, dim] # Save shell as xyz file - mol = Molecule(shell_species, positions, charge=-1) + mol = Molecule(shell_species, shell_pos, charge=-1) mol.to( os.path.join( save_dir, system_name, solute_atom, f"coord={c}", - f"size{k}_selection{ii}.xyz", + f"size{shell_size}_selection{idx}.xyz", ), "xyz", ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 74d39e4..0029f60 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -10,14 +10,14 @@ def rmsd(a, b): a: numpy array of positions, shape [N_atoms, 3] b: numpy array of positions, shape [N_atoms, 3] """ - return np.sqrt(np.mean(np.linalg.norm(b - a, axis=1))) + return np.sqrt(np.mean(np.sum((b - a)**2, axis=1))) def filter_by_rmsd(coords, n=20): """ - From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of RMSD" - - Because of the way that IonSolvR data is organized, should be able to just directly calculate rmsd on numpy coordinate arrays + From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum in-place RMSD. + Note: The Max-Min Diversity Problem is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords + by assuming that the point 0 is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we shuffled the order of coords, we would likely get a different result. Args: coords: list of np.ndarrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! @@ -26,12 +26,12 @@ def filter_by_rmsd(coords, n=20): """ states = {0} - min_rmsds = np.array([rmsd(coords[0], coords[i]) for i in range(len(coords))]) + min_rmsds = np.array([rmsd(coords[0], coord) for coord in coords]) for i in range(n - 1): best = np.argmax(min_rmsds) min_rmsds = np.minimum( min_rmsds, - np.array([rmsd(coords[best], coords[i]) for i in range(len(coords))]), + np.array([rmsd(coords[best], coord) for coord in coords]), ) states.add(best) From ef3e241cca938d75751b360d254f13db88d91cca Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 00:22:12 -0700 Subject: [PATCH 003/117] operate on pairwise distances, account for PBCs --- electrolytes/run_extraction.sh | 4 +-- electrolytes/solvation_shell_extract.py | 24 ++++++------- electrolytes/solvation_shell_utils.py | 48 +++++++++++++++++++------ 3 files changed, 49 insertions(+), 27 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index 1ccc233..b2d07cb 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -2,7 +2,7 @@ #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? # Run these scripts from om-data/electrolytes -python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ +python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ --save_dir 'results' \ --system_name 'NaCl_Water' \ --solute_atom 'NA0' \ @@ -10,7 +10,7 @@ python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electr --max_coord 5 \ --top_n 20 -python solvation_shell_extract.py --pdb_file_path '/home/sanjeevr/om-data/electrolytes/water_nacl_example.pdb' \ +python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ --save_dir 'results' \ --system_name 'NaCl_Water' \ --solute_atom 'CL0' \ diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 7678ed4..88c3fd9 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -10,7 +10,7 @@ from solvation_analysis.solute import Solute from solvation_analysis._column_names import * from pymatgen.core.structure import Molecule -from solvation_shell_utils import filter_by_rmsd +from solvation_shell_utils import filter_by_rmse, wrap_positions logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) @@ -107,7 +107,7 @@ def extract_solvation_shells( if len(shell.atoms.elements) > len(shell_species): shell_species = shell.atoms.elements - shell_positions.append(shell.atoms.positions) + shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) by_num_atoms = defaultdict(list) for sps in shell_positions: @@ -115,21 +115,17 @@ def extract_solvation_shells( # filter by number of atoms per shell selections_by_num_atoms = { - k: filter_by_rmsd(v, top_n) for k, v in by_num_atoms.items() + num_atoms: filter_by_rmse(shells_with_num_atoms, top_n) + for num_atoms, shells_with_num_atoms in by_num_atoms.items() } - for shell_size, shells in selections_by_num_atoms.items(): #loop over sizes - import pdb; pdb.set_trace() - for idx, shell_pos in enumerate(shells): + for ( + shell_size, + shell_positions, + ) in selections_by_num_atoms.items(): # loop over sizes + for idx, shell_pos in enumerate(shell_positions): if shell_pos.shape[0] == shell_species.shape[0]: - # Wrap positions - displacements = ( - shell_pos[:, np.newaxis, :] - shell_pos[np.newaxis, :, :] - ) - idx = np.where(displacements > lattices / 2)[0] - dim = np.where(displacements > lattices / 2)[2] - if idx.shape[0] > 0: - shell_pos[idx, dim] -= lattices[0, 0, dim] + # Save shell as xyz file mol = Molecule(shell_species, shell_pos, charge=-1) mol.to( diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 0029f60..2c9aa32 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -3,19 +3,20 @@ import numpy as np -def rmsd(a, b): +def rmse(a, b): """ - Compute the root mean squared distance between two sets of coordinates + Compute the root mean squared error between two sets of pairwise displacements Args: - a: numpy array of positions, shape [N_atoms, 3] - b: numpy array of positions, shape [N_atoms, 3] + a: numpy array of pairwise displacements, shape [N_atoms, N_atoms, 3] + b: numpy array of pairwise displacements, shape [N_atoms, N_atoms, 3] """ - return np.sqrt(np.mean(np.sum((b - a)**2, axis=1))) + return np.sqrt(np.mean(np.sum((b - a) ** 2, axis=2))) -def filter_by_rmsd(coords, n=20): +def filter_by_rmse(coords, n=20): """ - From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum in-place RMSD. + From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSE. + We operate on pairwise distances so that the function is invariant to translation and rotation. Note: The Max-Min Diversity Problem is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords by assuming that the point 0 is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we shuffled the order of coords, we would likely get a different result. @@ -24,23 +25,48 @@ def filter_by_rmsd(coords, n=20): Note that this latter requirement shouldn't be a problem, specifically when dealing with IonSolvR data. n: number of most diverse coordinates to return """ - + pairwise_disps = [ + coord[np.newaxis, :, :] - coord[:, np.newaxis, :] for coord in coords + ] states = {0} - min_rmsds = np.array([rmsd(coords[0], coord) for coord in coords]) - for i in range(n - 1): + min_rmsds = np.array( + [rmse(pairwise_disps[0], pairwise_disp) for pairwise_disp in pairwise_disps] + ) + for _ in range(n - 1): best = np.argmax(min_rmsds) min_rmsds = np.minimum( min_rmsds, - np.array([rmsd(coords[best], coord) for coord in coords]), + np.array( + [ + rmse(pairwise_disps[best], pairwise_disp) + for pairwise_disp in pairwise_disps + ] + ), ) states.add(best) return [coords[i] for i in states] +def wrap_positions(positions, lattices): + """ + Wraps input positions based on periodic boundary conditions. + Args: + positions: numpy array of positions, shape [N_atoms, 3] + lattices: numpy array representing dimensions of simulation box, shape [1, 1, 3] + """ + displacements = positions[:, np.newaxis, :] - positions[np.newaxis, :, :] + idx = np.where(displacements > lattices / 2)[0] + dim = np.where(displacements > lattices / 2)[2] + if idx.shape[0] > 0: + positions[idx, dim] -= lattices[0, 0, dim] + return positions + + def reorient(box_dimensions, coords, nsolute, solute_natoms, solvent_natoms): """ This function is not currently used in the pdb-file based solvation analysis + TODO: remove once Evan clarifies """ transforms = [ From f0922575376b4d84804472908d5c4478b49bd6b0 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 11:39:45 -0700 Subject: [PATCH 004/117] switch to kabsch rmsd --- electrolytes/solvation_shell_utils.py | 28 ++++++++------------------- 1 file changed, 8 insertions(+), 20 deletions(-) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 2c9aa32..e473575 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,22 +1,13 @@ import copy import itertools import numpy as np - - -def rmse(a, b): - """ - Compute the root mean squared error between two sets of pairwise displacements - Args: - a: numpy array of pairwise displacements, shape [N_atoms, N_atoms, 3] - b: numpy array of pairwise displacements, shape [N_atoms, N_atoms, 3] - """ - return np.sqrt(np.mean(np.sum((b - a) ** 2, axis=2))) +from rmsd import kabsch_rmsd def filter_by_rmse(coords, n=20): """ - From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSE. - We operate on pairwise distances so that the function is invariant to translation and rotation. + From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. + We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. Note: The Max-Min Diversity Problem is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords by assuming that the point 0 is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we shuffled the order of coords, we would likely get a different result. @@ -25,22 +16,17 @@ def filter_by_rmse(coords, n=20): Note that this latter requirement shouldn't be a problem, specifically when dealing with IonSolvR data. n: number of most diverse coordinates to return """ - pairwise_disps = [ - coord[np.newaxis, :, :] - coord[:, np.newaxis, :] for coord in coords - ] + states = {0} min_rmsds = np.array( - [rmse(pairwise_disps[0], pairwise_disp) for pairwise_disp in pairwise_disps] + [kabsch_rmsd(coords[0], coord, translate=True) for coord in coords] ) for _ in range(n - 1): best = np.argmax(min_rmsds) min_rmsds = np.minimum( min_rmsds, np.array( - [ - rmse(pairwise_disps[best], pairwise_disp) - for pairwise_disp in pairwise_disps - ] + [kabsch_rmsd(coords[best], coord, translate=True) for coord in coords] ), ) states.add(best) @@ -54,6 +40,8 @@ def wrap_positions(positions, lattices): Args: positions: numpy array of positions, shape [N_atoms, 3] lattices: numpy array representing dimensions of simulation box, shape [1, 1, 3] + Returns: + numpy array of wrapped_positions, shape [N_atoms, 3] """ displacements = positions[:, np.newaxis, :] - positions[np.newaxis, :, :] idx = np.where(displacements > lattices / 2)[0] From 14749ae83aeebff6563b8a6c9703e2c69e13e32e Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 11:41:39 -0700 Subject: [PATCH 005/117] add pdb file example --- .gitattributes | 2 ++ electrolytes/testfiles/water_nacl_example.pdb | 3 +++ 2 files changed, 5 insertions(+) create mode 100644 .gitattributes create mode 100644 electrolytes/testfiles/water_nacl_example.pdb diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..e8f121c --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +.pdb filter=lfs diff=lfs merge=lfs -text +*.pdb filter=lfs diff=lfs merge=lfs -text diff --git a/electrolytes/testfiles/water_nacl_example.pdb b/electrolytes/testfiles/water_nacl_example.pdb new file mode 100644 index 0000000..e1b5161 --- /dev/null +++ b/electrolytes/testfiles/water_nacl_example.pdb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a05fdde7fac9c8675aa6c923101b443b6ed49135fe32fbb8cdbea6dd1ada5c63 +size 439168525 From 42806705e64fc86a11ce2f518234655f4f068b58 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 15:11:13 -0700 Subject: [PATCH 006/117] add dependencies to setup --- electrolytes/solvation_shell_extract.py | 1 - setup.py | 11 ++++++++++- 2 files changed, 10 insertions(+), 2 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 88c3fd9..0920bb6 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -6,7 +6,6 @@ from collections import defaultdict import matplotlib.pyplot as plt import MDAnalysis as mda -import nglview as nv from solvation_analysis.solute import Solute from solvation_analysis._column_names import * from pymatgen.core.structure import Molecule diff --git a/setup.py b/setup.py index 27d4a54..c17fb66 100644 --- a/setup.py +++ b/setup.py @@ -12,6 +12,15 @@ description="Code for generating OMOL input configurations", url="http://github.com/Open-Catalyst-Project/om-data", packages=find_packages(), - install_requires=["ase", "quacc[sella]>=0.7.2"], + install_requires=[ + "ase", + "quacc[sella]>=0.7.2", + "numpy", + "tqdm", + "rmsd", + "MDAnalysis", + "pymatgen", + "solvation-analysis", + ], include_package_data=True, ) From 09031e290e43e0d42f2c2053905aa07092ea19ba Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 15:27:46 -0700 Subject: [PATCH 007/117] rename from rmse to rmsd --- electrolytes/solvation_shell_extract.py | 4 ++-- electrolytes/solvation_shell_utils.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 0920bb6..e6007fe 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -9,7 +9,7 @@ from solvation_analysis.solute import Solute from solvation_analysis._column_names import * from pymatgen.core.structure import Molecule -from solvation_shell_utils import filter_by_rmse, wrap_positions +from solvation_shell_utils import filter_by_rmsd, wrap_positions logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) @@ -114,7 +114,7 @@ def extract_solvation_shells( # filter by number of atoms per shell selections_by_num_atoms = { - num_atoms: filter_by_rmse(shells_with_num_atoms, top_n) + num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) for num_atoms, shells_with_num_atoms in by_num_atoms.items() } diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index e473575..27af5f3 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -4,7 +4,7 @@ from rmsd import kabsch_rmsd -def filter_by_rmse(coords, n=20): +def filter_by_rmsd(coords, n=20): """ From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. From 70de4e1fdf54cf9f67842e2a5ac1f346b3358ccc Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 15 May 2024 15:47:04 -0700 Subject: [PATCH 008/117] random seed for rmsd set instead of always starting at 0, remove reorient function --- electrolytes/solvation_shell_extract.py | 5 ++- electrolytes/solvation_shell_utils.py | 50 +++---------------------- 2 files changed, 9 insertions(+), 46 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index e6007fe..49a6248 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -1,6 +1,7 @@ import os import logging import argparse +import random import numpy as np from tqdm import tqdm from collections import defaultdict @@ -11,8 +12,6 @@ from pymatgen.core.structure import Molecule from solvation_shell_utils import filter_by_rmsd, wrap_positions -logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) - def extract_solvation_shells( pdb_file_path: str, @@ -140,6 +139,8 @@ def extract_solvation_shells( if __name__ == "__main__": + logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) + random.seed(10) parser = argparse.ArgumentParser() parser.add_argument("--pdb_file_path", type=str, help="PDB trajectory file path") diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 27af5f3..f478aff 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,6 +1,7 @@ import copy import itertools import numpy as np +import random from rmsd import kabsch_rmsd @@ -9,7 +10,7 @@ def filter_by_rmsd(coords, n=20): From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. Note: The Max-Min Diversity Problem is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords - by assuming that the point 0 is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we shuffled the order of coords, we would likely get a different result. + by assuming that the random seed point is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we ran this function multiple times, we would get different results. Args: coords: list of np.ndarrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! @@ -17,9 +18,10 @@ def filter_by_rmsd(coords, n=20): n: number of most diverse coordinates to return """ - states = {0} + seed_point = random.randint(0, len(coords) - 1) + states = {seed_point} min_rmsds = np.array( - [kabsch_rmsd(coords[0], coord, translate=True) for coord in coords] + [kabsch_rmsd(coords[seed_point], coord, translate=True) for coord in coords] ) for _ in range(n - 1): best = np.argmax(min_rmsds) @@ -48,44 +50,4 @@ def wrap_positions(positions, lattices): dim = np.where(displacements > lattices / 2)[2] if idx.shape[0] > 0: positions[idx, dim] -= lattices[0, 0, dim] - return positions - - -def reorient(box_dimensions, coords, nsolute, solute_natoms, solvent_natoms): - """ - This function is not currently used in the pdb-file based solvation analysis - TODO: remove once Evan clarifies - """ - - transforms = [ - np.array(x) * box_dimensions - for x in itertools.product([0, -1, 1], [0, -1, 1], [0, -1, 1]) - ] - - cog_solu = np.mean(coords[:solute_natoms], axis=0) - - n_solvents = int((len(coords) - nsolute * solute_natoms) / solvent_natoms) - - final_box = np.zeros(coords.shape) - final_box[: nsolute * solute_natoms] = coords[: nsolute * solute_natoms] - - for i in range(n_solvents): - min_dist = np.inf - best_coords = np.zeros((solvent_natoms, 3)) - - start_index = nsolute * solute_natoms + i * solvent_natoms - coords_i = coords[start_index : start_index + solvent_natoms] - assert len(coords_i) == solvent_natoms - - for transform in transforms: - coords_copy = copy.deepcopy(coords_i) - for i in range(solvent_natoms): - coords_copy[i] += transform - - cog_solv = np.mean(coords_copy, axis=0) - dist = np.linalg.norm(cog_solv - cog_solu) - if dist < min_dist: - min_dist = dist - best_coords = coords_copy - final_box[start_index : start_index + solvent_natoms] = best_coords - return final_box + return positions \ No newline at end of file From 3868637247b8b590597137aea18101a53b61db0c Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Thu, 16 May 2024 17:11:41 -0700 Subject: [PATCH 009/117] start adding support for multiatom solutes, not working yet --- electrolytes/run_extraction.sh | 20 +++++++++--------- electrolytes/solvation_shell_extract.py | 27 +++++++++++++++---------- 2 files changed, 26 insertions(+), 21 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index b2d07cb..a0c7dca 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -2,18 +2,18 @@ #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? # Run these scripts from om-data/electrolytes -python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ - --save_dir 'results' \ - --system_name 'NaCl_Water' \ - --solute_atom 'NA0' \ - --min_coord 2 \ - --max_coord 5 \ - --top_n 20 +# python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ +# --save_dir 'results' \ +# --system_name 'Al_ClO4' \ +# --solute_atoms 'AL0' \ +# --min_coord 2 \ +# --max_coord 5 \ +# --top_n 20 -python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ +python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ --save_dir 'results' \ - --system_name 'NaCl_Water' \ - --solute_atom 'CL0' \ + --system_name 'Al_ClO4' \ + --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ --min_coord 2 \ --max_coord 5 \ --top_n 20 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 49a6248..0c67df9 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -17,7 +17,7 @@ def extract_solvation_shells( pdb_file_path: str, save_dir: str, system_name: str, - solute_atom: str, + solute_atoms: str, min_coord: int, max_coord: int, top_n: int, @@ -36,9 +36,9 @@ def extract_solvation_shells( max_coord: Maximum coordination number to consider top_n: Number of snapshots to extract per coordination number. """ - + solute_atoms_name = ' '.join(solute_atoms) # Create save directory - os.makedirs(os.path.join(save_dir, system_name, solute_atom), exist_ok=True) + os.makedirs(os.path.join(save_dir, system_name, solute_atoms_name), exist_ok=True) # Initialize MDA Universe universe = mda.Universe(pdb_file_path) @@ -54,7 +54,9 @@ def extract_solvation_shells( lattices = np.array([a, b, c])[None][None] # Choose solute atom - solu = universe.select_atoms(f"name {solute_atom}") + # TODO: try to join multiple atoms in the same solute, doesn't currently work + query = ' or '.join(f'name {atom}' for atom in solute_atoms) + solu = universe.select_atoms(query) logging.info("Translating atoms to solute center of mass") for ts in tqdm(universe.trajectory): @@ -68,15 +70,17 @@ def extract_solvation_shells( solvent = universe.atoms - solu - solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name=solute_atom) + solv_anal = Solute.from_atoms(solu, {"solvent": solvent}) # Identify the cutoff for the first solvation shell, based on the MD trajectory logging.info("Running solvation analysis") + + #this line fails (can't find the radius) solv_anal.run() # Plot the RDF solv_anal.plot_solvation_radius("solute", "solvent") - plt.savefig(os.path.join(save_dir, system_name, solute_atom, "solvation_rdf.png")) + plt.savefig(os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png")) # There's probably a much faster way to do this # But for now, we're prototyping, so slow is okay @@ -89,7 +93,7 @@ def extract_solvation_shells( for c in range(min_coord, max_coord + 1): logging.info(f"Processing shells with coordination number {c}") os.makedirs( - os.path.join(save_dir, system_name, solute_atom, f"coord={c}"), + os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), exist_ok=True, ) shell_species = [] @@ -130,7 +134,7 @@ def extract_solvation_shells( os.path.join( save_dir, system_name, - solute_atom, + solute_atoms_name, f"coord={c}", f"size{shell_size}_selection{idx}.xyz", ), @@ -149,9 +153,10 @@ def extract_solvation_shells( "--system_name", type=str, help="Name of system used for directory naming" ) parser.add_argument( - "--solute_atom", + "--solute_atoms", type=str, - help="Which solute atom to extract solvation shells for", + nargs='+', + help="Which solute atom(s) to extract solvation shells for (accepts multiple values)", ) parser.add_argument( "--min_coord", type=int, help="Minimum shell coordination number to extract" @@ -172,7 +177,7 @@ def extract_solvation_shells( args.pdb_file_path, args.save_dir, args.system_name, - args.solute_atom, + args.solute_atoms, args.min_coord, args.max_coord, args.top_n, From 6b8e9a73fc1d4ba1f7d19032c2f283dfc18b109d Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Fri, 17 May 2024 11:08:11 -0700 Subject: [PATCH 010/117] fix star import, add al_cl04 test file --- electrolytes/.gitattributes | 1 + electrolytes/run_extraction.sh | 6 +++--- electrolytes/solvation_shell_extract.py | 2 +- electrolytes/testfiles/al_clo4_example.pdb | 3 +++ 4 files changed, 8 insertions(+), 4 deletions(-) create mode 100644 electrolytes/.gitattributes create mode 100644 electrolytes/testfiles/al_clo4_example.pdb diff --git a/electrolytes/.gitattributes b/electrolytes/.gitattributes new file mode 100644 index 0000000..515f1b0 --- /dev/null +++ b/electrolytes/.gitattributes @@ -0,0 +1 @@ +*pdb filter=lfs diff=lfs merge=lfs -text diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index a0c7dca..0d87f0f 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -10,10 +10,10 @@ # --max_coord 5 \ # --top_n 20 -python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ +python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ --save_dir 'results' \ - --system_name 'Al_ClO4' \ - --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ + --system_name 'NaCl' \ + --solute_atoms 'NA0' \ --min_coord 2 \ --max_coord 5 \ --top_n 20 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 0c67df9..532dca4 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -8,7 +8,7 @@ import matplotlib.pyplot as plt import MDAnalysis as mda from solvation_analysis.solute import Solute -from solvation_analysis._column_names import * +from solvation_analysis._column_names import FRAME, SOLUTE_IX from pymatgen.core.structure import Molecule from solvation_shell_utils import filter_by_rmsd, wrap_positions diff --git a/electrolytes/testfiles/al_clo4_example.pdb b/electrolytes/testfiles/al_clo4_example.pdb new file mode 100644 index 0000000..3e26fc8 --- /dev/null +++ b/electrolytes/testfiles/al_clo4_example.pdb @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dcb21506af983f64edc67be0482c08fbcca06cfadb05c115c33de6e66ea46879 +size 676734725 From 88832da32e13f6969d55899ca54973056c03f880 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Fri, 17 May 2024 11:12:31 -0700 Subject: [PATCH 011/117] update extraction script to be the non-working Al_Cl04 one --- electrolytes/run_extraction.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index 0d87f0f..a0c7dca 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -10,10 +10,10 @@ # --max_coord 5 \ # --top_n 20 -python solvation_shell_extract.py --pdb_file_path 'testfiles/water_nacl_example.pdb' \ +python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ --save_dir 'results' \ - --system_name 'NaCl' \ - --solute_atoms 'NA0' \ + --system_name 'Al_ClO4' \ + --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ --min_coord 2 \ --max_coord 5 \ --top_n 20 \ No newline at end of file From 0af4830390ee94878bd51165abc981fbddffa877 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 20 May 2024 10:21:32 -0700 Subject: [PATCH 012/117] correct charge assignment --- electrolytes/run_extraction.sh | 6 +- electrolytes/solvation_shell_extract.py | 35 +- electrolytes/solvation_shell_utils.py | 47 +- electrolytes/testfiles/Al_Cl04/system.data | 41322 ++++++++++++++++ electrolytes/testfiles/NaCl/system.data | 3036 ++ electrolytes/testfiles/al_clo4_example.pdb | 3 - electrolytes/testfiles/water_nacl_example.pdb | 3 - 7 files changed, 44427 insertions(+), 25 deletions(-) create mode 100644 electrolytes/testfiles/Al_Cl04/system.data create mode 100644 electrolytes/testfiles/NaCl/system.data delete mode 100644 electrolytes/testfiles/al_clo4_example.pdb delete mode 100644 electrolytes/testfiles/water_nacl_example.pdb diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index a0c7dca..b2c10c7 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -10,10 +10,10 @@ # --max_coord 5 \ # --top_n 20 -python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ +python solvation_shell_extract.py --input_dir 'testfiles/NaCl' \ --save_dir 'results' \ - --system_name 'Al_ClO4' \ - --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ + --system_name 'NaCl' \ + --solute_atoms 'NA0' \ --min_coord 2 \ --max_coord 5 \ --top_n 20 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 532dca4..144e85e 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -10,11 +10,15 @@ from solvation_analysis.solute import Solute from solvation_analysis._column_names import FRAME, SOLUTE_IX from pymatgen.core.structure import Molecule -from solvation_shell_utils import filter_by_rmsd, wrap_positions +from solvation_shell_utils import ( + filter_by_rmsd, + wrap_positions, + extract_charges_from_lammps_file, +) def extract_solvation_shells( - pdb_file_path: str, + input_dir: str, save_dir: str, system_name: str, solute_atoms: str, @@ -36,11 +40,16 @@ def extract_solvation_shells( max_coord: Maximum coordination number to consider top_n: Number of snapshots to extract per coordination number. """ - solute_atoms_name = ' '.join(solute_atoms) + solute_atoms_name = " ".join(solute_atoms) # Create save directory os.makedirs(os.path.join(save_dir, system_name, solute_atoms_name), exist_ok=True) + # Read charges from LAMMPS file + lammps_file_path = os.path.join(input_dir, "system.data") + charges = extract_charges_from_lammps_file(lammps_file_path) + # Initialize MDA Universe + pdb_file_path = os.path.join(input_dir, "system_output.pdb") universe = mda.Universe(pdb_file_path) # Add PBC box @@ -55,7 +64,7 @@ def extract_solvation_shells( # Choose solute atom # TODO: try to join multiple atoms in the same solute, doesn't currently work - query = ' or '.join(f'name {atom}' for atom in solute_atoms) + query = " or ".join(f"name {atom}" for atom in solute_atoms) solu = universe.select_atoms(query) logging.info("Translating atoms to solute center of mass") @@ -75,12 +84,14 @@ def extract_solvation_shells( # Identify the cutoff for the first solvation shell, based on the MD trajectory logging.info("Running solvation analysis") - #this line fails (can't find the radius) + # this line fails (can't find the radius) solv_anal.run() # Plot the RDF solv_anal.plot_solvation_radius("solute", "solvent") - plt.savefig(os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png")) + plt.savefig( + os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png") + ) # There's probably a much faster way to do this # But for now, we're prototyping, so slow is okay @@ -129,7 +140,7 @@ def extract_solvation_shells( if shell_pos.shape[0] == shell_species.shape[0]: # Save shell as xyz file - mol = Molecule(shell_species, shell_pos, charge=-1) + mol = Molecule(shell_species, shell_pos, charge=round(sum(charges))) mol.to( os.path.join( save_dir, @@ -147,7 +158,11 @@ def extract_solvation_shells( random.seed(10) parser = argparse.ArgumentParser() - parser.add_argument("--pdb_file_path", type=str, help="PDB trajectory file path") + parser.add_argument( + "--input_dir", + type=str, + help="Path containing PDB trajectory and LAMMPS data files", + ) parser.add_argument("--save_dir", type=str, help="Path to save xyz files") parser.add_argument( "--system_name", type=str, help="Name of system used for directory naming" @@ -155,7 +170,7 @@ def extract_solvation_shells( parser.add_argument( "--solute_atoms", type=str, - nargs='+', + nargs="+", help="Which solute atom(s) to extract solvation shells for (accepts multiple values)", ) parser.add_argument( @@ -174,7 +189,7 @@ def extract_solvation_shells( args = parser.parse_args() extract_solvation_shells( - args.pdb_file_path, + args.input_dir, args.save_dir, args.system_name, args.solute_atoms, diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index f478aff..c6b9e96 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,11 +1,11 @@ -import copy -import itertools +import re import numpy as np import random +from typing import List from rmsd import kabsch_rmsd -def filter_by_rmsd(coords, n=20): +def filter_by_rmsd(coords: List[np.array], n: int = 20) -> List[np.array]: """ From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. @@ -13,9 +13,11 @@ def filter_by_rmsd(coords, n=20): by assuming that the random seed point is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we ran this function multiple times, we would get different results. Args: - coords: list of np.ndarrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! + coords: list of np.arrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! Note that this latter requirement shouldn't be a problem, specifically when dealing with IonSolvR data. n: number of most diverse coordinates to return + Returns: + list of np.arrays of diverse atom coordinates """ seed_point = random.randint(0, len(coords) - 1) @@ -36,7 +38,7 @@ def filter_by_rmsd(coords, n=20): return [coords[i] for i in states] -def wrap_positions(positions, lattices): +def wrap_positions(positions: np.array, lattices: np.array) -> np.array: """ Wraps input positions based on periodic boundary conditions. Args: @@ -50,4 +52,37 @@ def wrap_positions(positions, lattices): dim = np.where(displacements > lattices / 2)[2] if idx.shape[0] > 0: positions[idx, dim] -= lattices[0, 0, dim] - return positions \ No newline at end of file + return positions + + +def extract_charges_from_lammps_file(file_path: str) -> List[float]: + """ + Extracts partial charges of each atom from a LAMMPS file. + Args: + file_path (str): path to the LAMMPS file + Returns: + charges: list of partial charges of length N_atoms + """ + with open(file_path, "r") as file: + lines = file.readlines() + + atoms_section = False + charges = [] + first = False + for line in lines: + if "Atoms" in line: + atoms_section = True + first = True + continue + if atoms_section: + if line.strip() == "": + if not first: + atoms_section = False + continue + first = False + parts = re.split(r"\s+", line.strip()) + # Assuming the format is: atom-ID molecule-ID atom-type charge x y z + charge = float(parts[3]) + charges.append(charge) + + return charges diff --git a/electrolytes/testfiles/Al_Cl04/system.data b/electrolytes/testfiles/Al_Cl04/system.data new file mode 100644 index 0000000..12256fd --- /dev/null +++ b/electrolytes/testfiles/Al_Cl04/system.data @@ -0,0 +1,41322 @@ +LAMMPS Description + + 8352 atoms + 7514 bonds + 12396 angles + 10250 dihedrals + 2750 impropers + + 24 atom types + 21 bond types + 35 angle types + 41 dihedral types + 11 improper types + + -25.0 25.0 xlo xhi + -25.0 25.0 ylo yhi + -25.0 25.0 zlo zhi + +Masses + +1 26.98 # Al +2 35.45 # Cl_clo4 +3 15.99 # O_clo4 +4 12.011 # type1_c_unk_edadc +5 12.011 # type2_c_unk_edadc +6 14.007 # type3_n_unk_edadc +7 12.011 # type4_c_unk_edadc +8 12.011 # type5_c_unk_edadc +9 14.007 # type6_n_unk_edadc +10 12.011 # type7_c_unk_edadc +11 12.011 # type8_c_unk_edadc +12 1.008 # type9_h_unk_edadc +13 1.008 # type10_h_unk_edadc +14 1.008 # type11_h_unk_edadc +15 1.008 # type12_h_unk_edadc +16 1.008 # type13_h_unk_edadc +17 1.008 # type14_h_unk_edadc +18 1.008 # type15_h_unk_edadc +19 1.008 # type16_h_unk_edadc +20 1.008 # type17_h_unk_edadc +21 1.008 # type18_h_unk_edadc +22 1.008 # type19_h_unk_edadc +23 10.811 # B_bf4 +24 18.998 # F_bf4 + +Atoms # full + +1 1 1 3 -7.204 19.755 -21.856 +2 2 1 3 23.168 -3.343 -8.082 +3 3 1 3 23.621 12.904 10.468 +4 4 1 3 -16.795 -9.498 18.083 +5 5 1 3 15.765 -23.923 0.169 +6 6 1 3 -21.458 21.119 6.393 +7 7 1 3 -13.419 -17.066 -18.994 +8 8 1 3 20.466 21.953 -14.837 +9 9 1 3 -25.001 -17.544 13.528 +10 10 1 3 -6.004 -24.168 -19.141 +11 11 1 3 18.543 9.622 22.699 +12 12 1 3 8.915 -16.403 -17.862 +13 13 1 3 17.866 11.961 -11.363 +14 14 1 3 -15.707 3.777 14.652 +15 15 1 3 -10.975 17.089 -6.733 +16 16 1 3 1.57 -16.147 -8.451 +17 17 1 3 -11.514 4.837 -19.732 +18 18 1 3 -19.866 11.137 -13.842 +19 19 1 3 15.525 20.687 8.287 +20 20 1 3 6.47 -20.266 -0.656 +21 21 1 3 -15.468 -14.129 15.583 +22 22 1 3 4.515 -21.505 20.79 +23 23 1 3 -14.164 -16.197 3.985 +24 24 1 3 10.957 6.439 8.019 +25 25 1 3 4.863 13.271 11.474 +26 26 1 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b/electrolytes/testfiles/water_nacl_example.pdb deleted file mode 100644 index e1b5161..0000000 --- a/electrolytes/testfiles/water_nacl_example.pdb +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:a05fdde7fac9c8675aa6c923101b443b6ed49135fe32fbb8cdbea6dd1ada5c63 -size 439168525 From 006c1ee6fef9c18fc48e4ddccb0389b329a6a888 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 31 May 2024 23:35:41 +0000 Subject: [PATCH 013/117] initial biolip_extraction --- biomolecules/pdb_pockets/biolip_extraction.py | 334 ++++++++++++++++++ 1 file changed, 334 insertions(+) create mode 100644 biomolecules/pdb_pockets/biolip_extraction.py diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py new file mode 100644 index 0000000..181c8b0 --- /dev/null +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -0,0 +1,334 @@ +import pandas as pd +import re +import os +import random +import subprocess +import glob +import shutil +import sys +from schrodinger.structure import StructureReader, StructureWriter +from schrodinger.structutils import build, analyze +from schrodinger.protein.captermini import CapTermini +from schrodinger.application import prepwizard +from schrodinger.adapter import evaluate_smarts + +SCHRO = "/opt/schrodinger2024-1" + + +def get_biolip_db(lig_type="reg"): + columns = [ + "pdb_id", + "receptor_chain", + "resolution", + "binding_site_number_code", + "ligand_id", + "ligand_chain", + "ligand_serial_number", + "binding_site_residues_pdb", + "binding_site_residues_re-numbered", + "catalytic_site_residues_pdb", + "catalytic_site_residues_re-numbered", + "ec_number", + "go_terms", + "binding_affinity_manual", + "binding_affinity_binding_moad", + "binding_affinity_pdbbind_cn", + "binding_affinity_bindingdb", + "uniprot_ids", + "pubmed_id", + "ligand_residue_number", + "receptor_sequence", + ] + types = {col: str for col in columns} + types["ligand_serial_number"] = int + biolip_df = pd.read_csv( + "/home/levineds/BioLiP.txt", + sep="\t", + names=columns, + dtype=types, + keep_default_na=False, + ) + biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ + "ligand_residue_number" + ].str.split("~", expand=True) + biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].fillna( + biolip_df["ligand_residue_number"] + ) + biolip_df[["ligand_residue_number", "ligand_residue_inscode"]] = biolip_df[ + "ligand_residue_number" + ].str.extract(r"(-?\d+)([A-Z\s]+)$") + biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].str.extract( + r"(-?\d+)" + ) + biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ + ["ligand_residue_number", "ligand_residue_end"] + ].astype(int) + # biolip_df.drop_duplicates(subset=['ligand_id', 'binding_site_residues_pdb'], inplace=True) + biolip_df["has_binding_info"] = ( + biolip_df[ + [ + "binding_affinity_manual", + "binding_affinity_binding_moad", + "binding_affinity_pdbbind_cn", + "binding_affinity_bindingdb", + ] + ] + != "" + ).any(axis=1) + + if lig_type == "macromol": + biolip_df = biolip_df[biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] + elif lig_type == "reg": + biolip_df = biolip_df[~biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] + return biolip_df + + +def retreive_ligand_and_env(biolip_df, ligand_size_limit=50, start_pdb=0, end_pdb=1000): + random.seed(12341) + grouped_biolip = biolip_df.groupby("pdb_id") + for pdb_count in range(start_pdb, end_pdb): + # pdb_id = random.choice(list(grouped_biolip.groups.keys())) + pdb_id = list(grouped_biolip.groups.keys())[pdb_count] + rows = grouped_biolip.get_group(pdb_id) + print(f"preparing {pdb_id} (entry: {pdb_count})") + sys.stdout.flush() + prepped_pdb_fnames = set() + for idx, row in rows.iterrows(): + try: + st, fname = get_prepped_protein(pdb_id, row) + except ValueError as e: + print(f"Error on {pdb_id}: Structure has only CA") + print(e) + continue + except RuntimeError as e: + print(f"Error on {pdb_id}: PrepWizard failed") + print(e) + continue + else: + prepped_pdb_fnames.add(fname) + binding_site_counter = ( + row["binding_site_number_code"] + row["receptor_chain"] + ) + try: + lig_ats, res_ats, st = get_atom_lists(st, row) + except RuntimeError as e: + print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") + print(e) + continue + heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] + if len(heavy_lig_ats) > ligand_size_limit: + print("ligand too big: ", len(heavy_lig_ats)) + continue + print(f"obtaining {pdb_id}, binding site {binding_site_counter}") + ligand_env = st.extract(lig_ats + res_ats) + try: + cap_termini(st, ligand_env) + except Exception as e: + print( + f"Error on {pdb_id}, BS{binding_site_counter}: Cannot cap termini" + ) + print(e) + continue + ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) + fname = f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb" + ligand_env.write(fname) + + # Cleanup the remaining prepped files for this pdb_id + for fname in prepped_pdb_fnames: + os.remove(fname) + + +def get_prepped_protein(pdb_id, row, prep=True): + baseoutname = f"{pdb_id}_prepped.maegz" + pdb_name = pdb_id + chains = {row["receptor_chain"], row["ligand_chain"]} + if len(chains) == 1: + solo_chain = next(iter(chains)) + pdb_name += f":{solo_chain}" + outname = f"{pdb_id}_{solo_chain}_prepped.maegz" + else: + outname = baseoutname + basename = pdb_name.replace(":", "_") + fname = basename + ".pdb" + + if not prep: + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) + outname = f"{pdb_id}.pdb" + elif os.path.exists(outname): + # We've already done this example + pass + elif os.path.exists(baseoutname): + # We've not done this chain, but we have done the whole protein + outname = baseoutname + else: + # We haven't done anything to prepare the protein + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_name]) + if not os.path.exists(fname): + # PDB could not be downloaded, try the cif + subprocess.run( + [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] + ) + st = StructureReader.read(f"{pdb_id}.cif") + # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours + at_list = [] + for chain in chains: + at_list.extend(st.chain[chain].getAtomList()) + st = st.extract(at_list) + fname = f"{pdb_id}.maegz" + with StructureWriter(fname) as writer: + writer.append(st) + st = StructureReader.read(fname) + # Reject structure that are just a bunch of CA + if ( + sum( + 1 + for mol in st.molecule + if len(mol.atom) == 1 and mol.atom[1].element == "C" + ) + > 20 + ): + raise ValueError + dummy_atoms = [at for at in st.atom if at.atomic_number < 1] + st.deleteAtoms(dummy_atoms) + st.write(fname) + subprocess.run( + [ + os.path.join(SCHRO, "utilities", "prepwizard"), + fname, + outname, + "-noepik", + "-noimpref", + "-fillsidechains", + "-disulfides", + "-NOJOBID", + ] + ) + if not os.path.exists(outname): + raise RuntimeError + + st = StructureReader.read(outname) + deprotonate_phosphate_esters(st) + st = build.reorder_protein_atoms_by_sequence(st) + + # Cleanup + for file_to_del in (fname, f"{pdb_id}.pdb", f"{pdb_id}.cif"): + if os.path.exists(file_to_del): + os.remove(file_to_del) + for deldir in glob.glob(f"{basename}-???"): + shutil.rmtree(deldir) + return st, outname + + +def deprotonate_phosphate_esters(st): + """ + At physiological pH, it's a good assumption that any phosphate esters + will be deprotonated. In the absence pKa's for ligands, we will make + this assumption. + """ + phos_smarts = "[*;!#1][*][P](=[O])([O])([O][H])" + matched_ats = evaluate_smarts(st, phos_smarts) + H_ats = {ats[-1] for ats in matched_ats} + O_ats = {ats[-2] for ats in matched_ats} + for O_at in O_ats: + st.atom[O_at].formal_charge -= 1 + st.deleteAtoms(H_ats) + + +def get_atom_lists(st, row, include_waters=False): + """ + Extract the ligand as its own chain. + + We extract a chain as DNA, RNA, peptides will have multiple residues. + We also include an option to extract waters in case we want the waters + associated with the ligand chain as well. + """ + res_ats = [] + res_list = [res[1:] for res in row["binding_site_residues_pdb"].split()] + gap_res = get_single_gaps(st, row["receptor_chain"], res_list) + for res_num in gap_res: + res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') + st_copy = st.copy() + if not res.isStandardResidue(): + ## You have to be pretty weird to not be a Standard Residue + continue + try: + build.mutate(st, res.getAlphaCarbon(), "GLY") + except: + # If the residue being turned to GLY is not just a simple amino + # acid, e.g. it is bound to a ligand, it can't be mutated properly + # and it will actually also garble the structure + st = st_copy + res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') + if res.getBetaCarbon() is not None: + st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) + build.mutate(st, res.getAlphaCarbon(), "GLY") + + # Mutating residues can change the atom numbering so out of an abundance + # of caution, let's retreive all the atom indices in a separate loop + for res_num in gap_res + res_list: + res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') + if res.hasMissingAtoms(): + print(f'Missing atoms in rec res {row["receptor_chain"]}:{res_num}') + raise RuntimeError + res_ats.extend(res.getAtomIndices()) + + lig_ats = [] + for res_num in range(row["ligand_residue_number"], row["ligand_residue_end"] + 1): + res_name = f'{row["ligand_chain"]}:{res_num}{row["ligand_residue_inscode"]}' + try: + res = st.findResidue(res_name) + except ValueError: + print(f"missing expected residue: {res_name}") + continue + lig_ats.extend(res.getAtomIndices()) + # Add in coodinating groups for ions + if len(lig_ats) == 1: + asl_str = f"fillres within 3 atom.num {lig_ats[0]}" + coord_ats = analyze.evaluate_asl(st, asl_str) + lig_ats.extend([at for at in coord_ats if at not in res_ats]) + + # mark the ligand chain + for at in lig_ats: + st.atom[at].chain = "ligand" + # mark the receptor chain + for at in res_ats: + st.atom[at].chain = "A" + + return lig_ats, res_ats, st + + +def get_single_gaps(st, rec_chain, res_list): + parent_indices = set() + parent_list = list(st.chain[rec_chain].residue) + for res_name in res_list: + res = st.findResidue(f"{rec_chain}:{res_name}") + parent_indices.add(parent_list.index(res)) + gaps = [ + val + 1 + for val in parent_indices + if val + 1 not in parent_indices and val + 2 in parent_indices + ] + gap_res = [f"{parent_list[gap].resnum}{parent_list[gap].inscode}" for gap in gaps] + return gap_res + + +def cap_termini(st, ligand_env): + capterm = CapTermini(ligand_env, verbose=False, frag_min_atoms=0) + for res in capterm.cappedResidues(): + orig_res = st.findResidue(res) + new_res = ligand_env.findResidue(res) + try: + val = st.measure(*orig_res.getDihedralAtoms("Psi")) + ligand_env.adjust(val, *new_res.getDihedralAtoms("Psi")) + + val = st.measure(*reversed(orig_res.getDihedralAtoms("Phi"))) + ligand_env.adjust(val, *reversed(new_res.getDihedralAtoms("Phi"))) + except: + pass + + +biolip_df = get_biolip_db() +batch_size = 1000 +start_pdb = int(sys.argv[1]) +end_pdb = int(sys.argv[2]) +ligand_env = retreive_ligand_and_env(biolip_df, start_pdb=start_pdb, end_pdb=end_pdb) From 53f52f96ac9ca5f536c97f9d4a2f27b500e6de5d Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 31 May 2024 23:35:57 +0000 Subject: [PATCH 014/117] metal-organics bug --- metal-organics/analyze_outputs.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/metal-organics/analyze_outputs.py b/metal-organics/analyze_outputs.py index 177c219..5fd07e2 100644 --- a/metal-organics/analyze_outputs.py +++ b/metal-organics/analyze_outputs.py @@ -8,7 +8,7 @@ def parse_args(): parser = argparse.ArgumentParser() - parse.add_argument("output_path") + parser.add_argument("output_path") return parser.parse_args() From 869b81ae76f62e23c17ecbb0df2b388f9c495f71 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 31 May 2024 23:41:51 +0000 Subject: [PATCH 015/117] minor changes --- biomolecules/pdb_pockets/biolip_extraction.py | 24 ++++++++++++------- 1 file changed, 16 insertions(+), 8 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 181c8b0..9fee85a 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -42,7 +42,7 @@ def get_biolip_db(lig_type="reg"): types = {col: str for col in columns} types["ligand_serial_number"] = int biolip_df = pd.read_csv( - "/home/levineds/BioLiP.txt", + "BioLiP_05_31_2024.txt", sep="\t", names=columns, dtype=types, @@ -63,7 +63,9 @@ def get_biolip_db(lig_type="reg"): biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ ["ligand_residue_number", "ligand_residue_end"] ].astype(int) - # biolip_df.drop_duplicates(subset=['ligand_id', 'binding_site_residues_pdb'], inplace=True) + biolip_df.drop_duplicates( + subset=["ligand_id", "binding_site_residues_pdb"], inplace=True + ) biolip_df["has_binding_info"] = ( biolip_df[ [ @@ -281,7 +283,7 @@ def get_atom_lists(st, row, include_waters=False): print(f"missing expected residue: {res_name}") continue lig_ats.extend(res.getAtomIndices()) - # Add in coodinating groups for ions + # Add in coordinating groups for ions if len(lig_ats) == 1: asl_str = f"fillres within 3 atom.num {lig_ats[0]}" coord_ats = analyze.evaluate_asl(st, asl_str) @@ -327,8 +329,14 @@ def cap_termini(st, ligand_env): pass -biolip_df = get_biolip_db() -batch_size = 1000 -start_pdb = int(sys.argv[1]) -end_pdb = int(sys.argv[2]) -ligand_env = retreive_ligand_and_env(biolip_df, start_pdb=start_pdb, end_pdb=end_pdb) +def main(): + biolip_df = get_biolip_db() + start_pdb = int(sys.argv[1]) + end_pdb = int(sys.argv[2]) + ligand_env = retreive_ligand_and_env( + biolip_df, start_pdb=start_pdb, end_pdb=end_pdb + ) + + +if __name__ == "__main__": + main() From bdcb5888304b4dc7ecbc4f674a063862064dae88 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 4 Jun 2024 17:27:47 +0000 Subject: [PATCH 016/117] refactor make_gaps_gly --- biomolecules/pdb_pockets/biolip_extraction.py | 56 ++++++++++++------- 1 file changed, 37 insertions(+), 19 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 9fee85a..019829c 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -112,7 +112,7 @@ def retreive_ligand_and_env(biolip_df, ligand_size_limit=50, start_pdb=0, end_pd row["binding_site_number_code"] + row["receptor_chain"] ) try: - lig_ats, res_ats, st = get_atom_lists(st, row) + lig_ats, res_ats = get_atom_lists(st, row) except RuntimeError as e: print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") print(e) @@ -235,6 +235,40 @@ def deprotonate_phosphate_esters(st): st.atom[O_at].formal_charge -= 1 st.deleteAtoms(H_ats) +def make_gaps_gly(st, gap_res): + """ + Turn gap residues into glycines + + If we have a single residue which would not normally be included + which is between two which are, then the capping groups of those + two are going to overlap because they are both trying to fill in + the same missing CA. As such, we should just include that missing + single gap residue as a glycine (it's actually smaller than two + capping groups). + + If that gap residue is something non-standard (and Schrodinger + considers a lot more than the 20 standard amino acids to be + "standard", e.g. selenomethionine, hydroxyproline are "standard"), + we just leave it as is. + + :param st: Structure being modified + :param gap_res: list of residue numbers which are single gaps + """ + for res_num in gap_res: + res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') + ## You have to be pretty weird to not be a Standard Residue, + ## just keep these as is + if not res.isStandardResidue(): + continue + # If the residue being turned to GLY is not just a simple amino + # acid, e.g. it is bound to a ligand, it can't be mutated properly + # and it will actually also garble the structure + if res.getBetaCarbon() is not None: + st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) + try: + build.mutate(st, res.getAlphaCarbon(), "GLY") + except: + continue def get_atom_lists(st, row, include_waters=False): """ @@ -247,23 +281,7 @@ def get_atom_lists(st, row, include_waters=False): res_ats = [] res_list = [res[1:] for res in row["binding_site_residues_pdb"].split()] gap_res = get_single_gaps(st, row["receptor_chain"], res_list) - for res_num in gap_res: - res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') - st_copy = st.copy() - if not res.isStandardResidue(): - ## You have to be pretty weird to not be a Standard Residue - continue - try: - build.mutate(st, res.getAlphaCarbon(), "GLY") - except: - # If the residue being turned to GLY is not just a simple amino - # acid, e.g. it is bound to a ligand, it can't be mutated properly - # and it will actually also garble the structure - st = st_copy - res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') - if res.getBetaCarbon() is not None: - st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) - build.mutate(st, res.getAlphaCarbon(), "GLY") + make_gaps_gly(st, gap_res) # Mutating residues can change the atom numbering so out of an abundance # of caution, let's retreive all the atom indices in a separate loop @@ -296,7 +314,7 @@ def get_atom_lists(st, row, include_waters=False): for at in res_ats: st.atom[at].chain = "A" - return lig_ats, res_ats, st + return lig_ats, res_ats def get_single_gaps(st, rec_chain, res_list): From 4a3fcc8213db1891c80ffcd3017c69650b1bb53c Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 4 Jun 2024 20:39:13 +0000 Subject: [PATCH 017/117] Add memory estimate function --- omdata/orca/calc.py | 118 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 118 insertions(+) diff --git a/omdata/orca/calc.py b/omdata/orca/calc.py index 2eccddb..717bcf0 100644 --- a/omdata/orca/calc.py +++ b/omdata/orca/calc.py @@ -12,6 +12,94 @@ **{i: 28 for i in range(58, 72)}, **{i: 60 for i in range(72, 87)}, } +BASIS_DICT = { + "H": 9, + "He": 9, + "Li": 17, + "Be": 22, + "B": 37, + "C": 37, + "N": 37, + "O": 40, + "F": 40, + "Ne": 40, + "Na": 35, + "Mg": 35, + "Al": 43, + "Si": 43, + "P": 43, + "S": 46, + "Cl": 46, + "Ar": 46, + "K": 36, + "Ca": 36, + "Sc": 48, + "Ti": 48, + "V": 48, + "Cr": 48, + "Mn": 48, + "Fe": 48, + "Co": 48, + "Ni": 48, + "Cu": 48, + "Zn": 51, + "Ga": 54, + "Ge": 54, + "As": 54, + "Se": 57, + "Br": 57, + "Kr": 57, + "Rb": 33, + "Sr": 33, + "Y": 40, + "Zr": 40, + "Nb": 40, + "Mo": 40, + "Tc": 40, + "Ru": 40, + "Rh": 40, + "Pd": 40, + "Ag": 40, + "Cd": 40, + "In": 56, + "Sn": 56, + "Sb": 56, + "Te": 59, + "I": 59, + "Xe": 59, + "Cs": 32, + "Ba": 40, + "La": 43, + "Ce": 105, + "Pr": 105, + "Nd": 98, + "Pm": 98, + "Sm": 98, + "Eu": 93, + "Gd": 98, + "Tb": 98, + "Dy": 98, + "Ho": 98, + "Er": 101, + "Tm": 101, + "Yb": 96, + "Lu": 96, + "Hf": 43, + "Ta": 43, + "W": 43, + "Re": 43, + "Os": 43, + "Ir": 43, + "Pt": 43, + "Au": 43, + "Hg": 46, + "Tl": 56, + "Pb": 56, + "Bi": 56, + "Po": 59, + "At": 59, + "Rn": 59, +} ORCA_FUNCTIONAL = "wB97M-V" ORCA_BASIS = "def2-TZVPD" @@ -75,6 +163,36 @@ def get_symm_break_block(atoms: Atoms, charge: int) -> str: return f"%scf rotate {{{lumo-1}, {lumo}, 20, 1, 1}} end end" +def get_n_basis(atoms: Atoms) -> int: + """ + Get the number of basis functions that will be used for the given input. + + We assume our basis is def2-tzvpd. The number of basis functions is used + to estimate the memory requirments of a given job. + """ + nbasis = 0 + for elt in atoms.get_chemical_symbols(): + nbasis += BASIS_DICT[elt] + return nbasis + + +def get_mem_estimate(atoms: Atoms, vertical=Vertical.Default, mult=1): + """ + Get an estimate of the memory requirement for given input in MB. + + If the estimate is less than 1000MB, we return 1000MB. + """ + nbasis = get_n_basis(atoms) + if vertical == Vertical.Default and mult == 1: + a = 0.013060654016809259 + b = -145.62585242047592 + else: + a = 0.016460518374501867 + b = -320.38502508802776 + mem_est = max(a * nbasis**1.5 + b, 1000) + return mem_est + + def write_orca_inputs( atoms: Atoms, output_directory, From 3e5ce546a73aef47ffb38bf0cafd070f54fb55ac Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 4 Jun 2024 20:42:34 +0000 Subject: [PATCH 018/117] docstrings --- omdata/orca/calc.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/omdata/orca/calc.py b/omdata/orca/calc.py index 717bcf0..d0ee0a9 100644 --- a/omdata/orca/calc.py +++ b/omdata/orca/calc.py @@ -169,6 +169,9 @@ def get_n_basis(atoms: Atoms) -> int: We assume our basis is def2-tzvpd. The number of basis functions is used to estimate the memory requirments of a given job. + + :param atoms: atoms to compute the number of basis functions of + :return: number of basis functions as printed by Orca """ nbasis = 0 for elt in atoms.get_chemical_symbols(): @@ -176,11 +179,17 @@ def get_n_basis(atoms: Atoms) -> int: return nbasis -def get_mem_estimate(atoms: Atoms, vertical=Vertical.Default, mult=1): +def get_mem_estimate(atoms: Atoms, vertical=Vertical.Default, mult=1) -> int: """ Get an estimate of the memory requirement for given input in MB. If the estimate is less than 1000MB, we return 1000MB. + + :param atoms: atoms to compute the number of basis functions of + :param vertical: Which vertical this is for (all metal-organics are + UKS, as are all regular open-shell calcs) + :param mult: spin multiplicity of input + :return: estimated (upper-bound) to the memory requirement of this Orca job """ nbasis = get_n_basis(atoms) if vertical == Vertical.Default and mult == 1: From 6d327fc2f8172f982a5df0fda9b84ed6326d7526 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 16:53:45 +0000 Subject: [PATCH 019/117] Refactor --- biomolecules/pdb_pockets/biolip_extraction.py | 200 +++++++++++++----- 1 file changed, 144 insertions(+), 56 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 019829c..aaf43e1 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -15,7 +15,19 @@ SCHRO = "/opt/schrodinger2024-1" -def get_biolip_db(lig_type="reg"): +class OnlyCAError(Exception): + pass + + +class MissingAtomsError(Exception): + pass + + +class MissingResiduesError(Exception): + pass + + +def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: columns = [ "pdb_id", "receptor_chain", @@ -85,22 +97,39 @@ def get_biolip_db(lig_type="reg"): return biolip_df -def retreive_ligand_and_env(biolip_df, ligand_size_limit=50, start_pdb=0, end_pdb=1000): - random.seed(12341) +def retreive_ligand_and_env( + biolip_df: pd.DataFrame, + ligand_size_limit: int = 50, + start_pdb: int = 0, + end_pdb: int = 1000, +) -> None: + """ + Extract ligand and its environment from BioLiP examples + + Procedure is as follows, for each protein in BioLiP: + 1) Download the structure and prepare it with PrepWizard (re-using already prepared proteins if possible) + 2) Obtain list of atoms which are assigned as ligands or receptors in BioLiP + 3) Extract the receptor residues and cap them to match the source protein + 4) Write the extracted structure to a pdb file + """ + # random.seed(12341) grouped_biolip = biolip_df.groupby("pdb_id") + pdb_list = list(grouped_biolip.groups.keys()) for pdb_count in range(start_pdb, end_pdb): # pdb_id = random.choice(list(grouped_biolip.groups.keys())) - pdb_id = list(grouped_biolip.groups.keys())[pdb_count] + pdb_id = pdb_list[pdb_count] rows = grouped_biolip.get_group(pdb_id) print(f"preparing {pdb_id} (entry: {pdb_count})") sys.stdout.flush() prepped_pdb_fnames = set() for idx, row in rows.iterrows(): + binding_site_counter = ( + row["binding_site_number_code"] + row["receptor_chain"] + ) try: st, fname = get_prepped_protein(pdb_id, row) - except ValueError as e: + except OnlyCAError: print(f"Error on {pdb_id}: Structure has only CA") - print(e) continue except RuntimeError as e: print(f"Error on {pdb_id}: PrepWizard failed") @@ -108,19 +137,20 @@ def retreive_ligand_and_env(biolip_df, ligand_size_limit=50, start_pdb=0, end_pd continue else: prepped_pdb_fnames.add(fname) - binding_site_counter = ( - row["binding_site_number_code"] + row["receptor_chain"] - ) + try: lig_ats, res_ats = get_atom_lists(st, row) - except RuntimeError as e: + except MissingAtomsError: print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") - print(e) continue + + # Count heavy atoms of ligand and skip if too large heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] if len(heavy_lig_ats) > ligand_size_limit: print("ligand too big: ", len(heavy_lig_ats)) continue + + # Do the extraction print(f"obtaining {pdb_id}, binding site {binding_site_counter}") ligand_env = st.extract(lig_ats + res_ats) try: @@ -140,6 +170,34 @@ def retreive_ligand_and_env(biolip_df, ligand_size_limit=50, start_pdb=0, end_pd os.remove(fname) +def download_cif(pdb_id, chains): + subprocess.run( + [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] + ) + st = StructureReader.read(f"{pdb_id}.cif") + # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours + at_list = [] + for chain in chains: + at_list.extend(st.chain[chain].getAtomList()) + st = st.extract(at_list) + fname = f"{pdb_id}.maegz" + with StructureWriter(fname) as writer: + writer.append(st) + return fname + + +def missing_backbone_check(st): + if ( + sum( + 1 + for mol in st.molecule + if len(mol.atom) == 1 and mol.atom[1].element == "C" + ) + > 20 + ): + raise OnlyCAError + + def get_prepped_protein(pdb_id, row, prep=True): baseoutname = f"{pdb_id}_prepped.maegz" pdb_name = pdb_id @@ -167,46 +225,23 @@ def get_prepped_protein(pdb_id, row, prep=True): subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_name]) if not os.path.exists(fname): # PDB could not be downloaded, try the cif - subprocess.run( - [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] - ) - st = StructureReader.read(f"{pdb_id}.cif") - # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours - at_list = [] - for chain in chains: - at_list.extend(st.chain[chain].getAtomList()) - st = st.extract(at_list) - fname = f"{pdb_id}.maegz" - with StructureWriter(fname) as writer: - writer.append(st) + fname = download_cif(pdb_id, chains) st = StructureReader.read(fname) # Reject structure that are just a bunch of CA - if ( - sum( - 1 - for mol in st.molecule - if len(mol.atom) == 1 and mol.atom[1].element == "C" - ) - > 20 - ): - raise ValueError + missing_backbone_check(st) + + # Remove any dummy atoms, PrepWizard doesn't like them dummy_atoms = [at for at in st.atom if at.atomic_number < 1] st.deleteAtoms(dummy_atoms) st.write(fname) - subprocess.run( - [ - os.path.join(SCHRO, "utilities", "prepwizard"), - fname, - outname, - "-noepik", - "-noimpref", - "-fillsidechains", - "-disulfides", - "-NOJOBID", - ] - ) + + # Run PrepWizard + try: + run_prepwizard(fname, outname) + except subprocess.TimeoutExpired: + raise RuntimeError('PrepWizard took longer than 2 hours, skipping') if not os.path.exists(outname): - raise RuntimeError + raise RuntimeError('PrepWizard failed') st = StructureReader.read(outname) deprotonate_phosphate_esters(st) @@ -220,6 +255,38 @@ def get_prepped_protein(pdb_id, row, prep=True): shutil.rmtree(deldir) return st, outname +def run_prepwizard(fname, outname): + try: + subprocess.run( + [ + os.path.join(SCHRO, "utilities", "prepwizard"), + fname, + outname, + "-noepik", + "-noimpref", + "-fillsidechains", + "-disulfides", + "-NOJOBID", + ], + timeout=3600*2 # Wait not more than 2 hours + ) + except subprocess.TimeoutExpired as e: + # Try again without PROPKA (which seems to be where things get stuck) + subprocess.run( + [ + os.path.join(SCHRO, "utilities", "prepwizard"), + fname, + outname, + "-noepik", + "-noimpref", + "-fillsidechains", + "-disulfides", + "-nopropka", + "-NOJOBID", + ], + timeout=3600*2 # Wait not more than 2 hours + ) + def deprotonate_phosphate_esters(st): """ @@ -235,7 +302,8 @@ def deprotonate_phosphate_esters(st): st.atom[O_at].formal_charge -= 1 st.deleteAtoms(H_ats) -def make_gaps_gly(st, gap_res): + +def make_gaps_gly(st, row, gap_res): """ Turn gap residues into glycines @@ -265,10 +333,8 @@ def make_gaps_gly(st, gap_res): # and it will actually also garble the structure if res.getBetaCarbon() is not None: st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) - try: - build.mutate(st, res.getAlphaCarbon(), "GLY") - except: - continue + build.mutate(st, res.getAlphaCarbon(), "GLY") + def get_atom_lists(st, row, include_waters=False): """ @@ -281,15 +347,15 @@ def get_atom_lists(st, row, include_waters=False): res_ats = [] res_list = [res[1:] for res in row["binding_site_residues_pdb"].split()] gap_res = get_single_gaps(st, row["receptor_chain"], res_list) - make_gaps_gly(st, gap_res) + make_gaps_gly(st, row, gap_res) - # Mutating residues can change the atom numbering so out of an abundance - # of caution, let's retreive all the atom indices in a separate loop + # Mutating residues can change the atom numbering so let's retreive + # all the atom indices in a separate loop for res_num in gap_res + res_list: res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') if res.hasMissingAtoms(): print(f'Missing atoms in rec res {row["receptor_chain"]}:{res_num}') - raise RuntimeError + raise MissingAtomsError res_ats.extend(res.getAtomIndices()) lig_ats = [] @@ -297,7 +363,7 @@ def get_atom_lists(st, row, include_waters=False): res_name = f'{row["ligand_chain"]}:{res_num}{row["ligand_residue_inscode"]}' try: res = st.findResidue(res_name) - except ValueError: + except MissingResiduesError: print(f"missing expected residue: {res_name}") continue lig_ats.extend(res.getAtomIndices()) @@ -309,7 +375,7 @@ def get_atom_lists(st, row, include_waters=False): # mark the ligand chain for at in lig_ats: - st.atom[at].chain = "ligand" + st.atom[at].chain = "l" # mark the receptor chain for at in res_ats: st.atom[at].chain = "A" @@ -318,6 +384,21 @@ def get_atom_lists(st, row, include_waters=False): def get_single_gaps(st, rec_chain, res_list): + """ + Get residues that are not in a list of residues but are + between two residues which are in the list. + + If we have a single residue which would not normally be included + which is between two which are, then the capping groups of those + two are going to overlap because they are both trying to fill in + the same missing CA (the CA of the gap residue). We need to treat + these specially so we retrieve them here. + + :param st: structure to analyze + :param rec_chain: name of receptor chain + :param res_list: list of residue names which may have single-residue gaps + :return: list of residues which are single-residue gaps in `res_list` + """ parent_indices = set() parent_list = list(st.chain[rec_chain].residue) for res_name in res_list: @@ -333,6 +414,13 @@ def get_single_gaps(st, rec_chain, res_list): def cap_termini(st, ligand_env): + """ + Cap termini for extracted receptor chains with NMA or ACE oriented to match + the positions of neighboring residues in the original structure. + + :param st: original protein structure from which the pocket was extracted + :param ligand_env: extracted protein receptor (i.e. ligand environment) + """ capterm = CapTermini(ligand_env, verbose=False, frag_min_atoms=0) for res in capterm.cappedResidues(): orig_res = st.findResidue(res) From e3182e6a186220e3813608dce15a28d9323bdf3c Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 17:12:27 +0000 Subject: [PATCH 020/117] docstrings --- biomolecules/pdb_pockets/biolip_extraction.py | 60 ++++++++++++++----- 1 file changed, 46 insertions(+), 14 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index aaf43e1..4412dc1 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -6,7 +6,7 @@ import glob import shutil import sys -from schrodinger.structure import StructureReader, StructureWriter +from schrodinger.structure import Structure, StructureReader, StructureWriter from schrodinger.structutils import build, analyze from schrodinger.protein.captermini import CapTermini from schrodinger.application import prepwizard @@ -170,7 +170,15 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id, chains): +def download_cif(pdb_id:str, chains:list[str]) -> str: + """ + Download cif (as opposed to pdb) of a given protein and extract + the needed chains. + + :param pdb_id: name of PDB to download + :param chains: list of relevant chain names to extract + :return: filename where structure has been downloaded + """ subprocess.run( [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] ) @@ -186,7 +194,17 @@ def download_cif(pdb_id, chains): return fname -def missing_backbone_check(st): +def missing_backbone_check(st: Structure): + """ + Check if the protein backbone is present in the structure + + Rarely, some protein structures are just C alpha positions. We check + for this by making sure that the structure doesn't contain lots of + isolated carbon atoms. + + :param st: structure to check + :raises: OnlyCAError if structure seems like it is only CA + """ if ( sum( 1 @@ -198,7 +216,7 @@ def missing_backbone_check(st): raise OnlyCAError -def get_prepped_protein(pdb_id, row, prep=True): +def get_prepped_protein(pdb_id:str, row:pd.Series, prep:bool=True) -> tuple[Structure, str]: baseoutname = f"{pdb_id}_prepped.maegz" pdb_name = pdb_id chains = {row["receptor_chain"], row["ligand_chain"]} @@ -255,7 +273,19 @@ def get_prepped_protein(pdb_id, row, prep=True): shutil.rmtree(deldir) return st, outname -def run_prepwizard(fname, outname): +def run_prepwizard(fname: str, outname: str) -> None: + """ + Run Schrodinger's PrepWizard + + In most cases, this seems to run in a handful of seconds to a few minutes. + In a few extreme examples, it took hours or days. Since this holds up processing + for the entire batch, we will add a 2 hour time-limit with PROPKA and an additional + 2 hour time-limit not using PROPKA (which seems to frequently be were things get bogged + down, though it may also be in H-Bond optimization). + + :param fname: input file name for PrepWizard + :param outname: output file name from PrepWizard + """ try: subprocess.run( [ @@ -288,11 +318,13 @@ def run_prepwizard(fname, outname): ) -def deprotonate_phosphate_esters(st): +def deprotonate_phosphate_esters(st: Structure) -> None: """ At physiological pH, it's a good assumption that any phosphate esters will be deprotonated. In the absence pKa's for ligands, we will make this assumption. + + :param st: Structure with phosphate groups that can be deprotonated """ phos_smarts = "[*;!#1][*][P](=[O])([O])([O][H])" matched_ats = evaluate_smarts(st, phos_smarts) @@ -303,7 +335,7 @@ def deprotonate_phosphate_esters(st): st.deleteAtoms(H_ats) -def make_gaps_gly(st, row, gap_res): +def make_gaps_gly(st: Structure, row: pd.Series, gap_res:list[str]) -> None: """ Turn gap residues into glycines @@ -320,6 +352,7 @@ def make_gaps_gly(st, row, gap_res): we just leave it as is. :param st: Structure being modified + :param row: Series containing receptor and ligand information :param gap_res: list of residue numbers which are single gaps """ for res_num in gap_res: @@ -336,13 +369,12 @@ def make_gaps_gly(st, row, gap_res): build.mutate(st, res.getAlphaCarbon(), "GLY") -def get_atom_lists(st, row, include_waters=False): +def get_atom_lists(st:Structure, row: pd.Series) -> tuple[list[int], list[int]]: """ - Extract the ligand as its own chain. + Get the lists of ligand atoms and receptor atoms - We extract a chain as DNA, RNA, peptides will have multiple residues. - We also include an option to extract waters in case we want the waters - associated with the ligand chain as well. + :param st: Structure to extract from + :param row: Series containing receptor and ligand information """ res_ats = [] res_list = [res[1:] for res in row["binding_site_residues_pdb"].split()] @@ -383,7 +415,7 @@ def get_atom_lists(st, row, include_waters=False): return lig_ats, res_ats -def get_single_gaps(st, rec_chain, res_list): +def get_single_gaps(st:Structure, rec_chain:str, res_list:list[str]) -> list[str]: """ Get residues that are not in a list of residues but are between two residues which are in the list. @@ -413,7 +445,7 @@ def get_single_gaps(st, rec_chain, res_list): return gap_res -def cap_termini(st, ligand_env): +def cap_termini(st: Structure, ligand_env: Structure) -> None: """ Cap termini for extracted receptor chains with NMA or ACE oriented to match the positions of neighboring residues in the original structure. From 2401268d6085eb91ff3c7f76b1e8081aec542e9d Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 17:13:05 +0000 Subject: [PATCH 021/117] black --- biomolecules/pdb_pockets/biolip_extraction.py | 23 +++++++++++-------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 4412dc1..11ec323 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -170,7 +170,7 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id:str, chains:list[str]) -> str: +def download_cif(pdb_id: str, chains: list[str]) -> str: """ Download cif (as opposed to pdb) of a given protein and extract the needed chains. @@ -216,7 +216,9 @@ def missing_backbone_check(st: Structure): raise OnlyCAError -def get_prepped_protein(pdb_id:str, row:pd.Series, prep:bool=True) -> tuple[Structure, str]: +def get_prepped_protein( + pdb_id: str, row: pd.Series, prep: bool = True +) -> tuple[Structure, str]: baseoutname = f"{pdb_id}_prepped.maegz" pdb_name = pdb_id chains = {row["receptor_chain"], row["ligand_chain"]} @@ -257,9 +259,9 @@ def get_prepped_protein(pdb_id:str, row:pd.Series, prep:bool=True) -> tuple[Stru try: run_prepwizard(fname, outname) except subprocess.TimeoutExpired: - raise RuntimeError('PrepWizard took longer than 2 hours, skipping') + raise RuntimeError("PrepWizard took longer than 2 hours, skipping") if not os.path.exists(outname): - raise RuntimeError('PrepWizard failed') + raise RuntimeError("PrepWizard failed") st = StructureReader.read(outname) deprotonate_phosphate_esters(st) @@ -273,6 +275,7 @@ def get_prepped_protein(pdb_id:str, row:pd.Series, prep:bool=True) -> tuple[Stru shutil.rmtree(deldir) return st, outname + def run_prepwizard(fname: str, outname: str) -> None: """ Run Schrodinger's PrepWizard @@ -298,7 +301,7 @@ def run_prepwizard(fname: str, outname: str) -> None: "-disulfides", "-NOJOBID", ], - timeout=3600*2 # Wait not more than 2 hours + timeout=3600 * 2, # Wait not more than 2 hours ) except subprocess.TimeoutExpired as e: # Try again without PROPKA (which seems to be where things get stuck) @@ -314,9 +317,9 @@ def run_prepwizard(fname: str, outname: str) -> None: "-nopropka", "-NOJOBID", ], - timeout=3600*2 # Wait not more than 2 hours + timeout=3600 * 2, # Wait not more than 2 hours ) - + def deprotonate_phosphate_esters(st: Structure) -> None: """ @@ -335,7 +338,7 @@ def deprotonate_phosphate_esters(st: Structure) -> None: st.deleteAtoms(H_ats) -def make_gaps_gly(st: Structure, row: pd.Series, gap_res:list[str]) -> None: +def make_gaps_gly(st: Structure, row: pd.Series, gap_res: list[str]) -> None: """ Turn gap residues into glycines @@ -369,7 +372,7 @@ def make_gaps_gly(st: Structure, row: pd.Series, gap_res:list[str]) -> None: build.mutate(st, res.getAlphaCarbon(), "GLY") -def get_atom_lists(st:Structure, row: pd.Series) -> tuple[list[int], list[int]]: +def get_atom_lists(st: Structure, row: pd.Series) -> tuple[list[int], list[int]]: """ Get the lists of ligand atoms and receptor atoms @@ -415,7 +418,7 @@ def get_atom_lists(st:Structure, row: pd.Series) -> tuple[list[int], list[int]]: return lig_ats, res_ats -def get_single_gaps(st:Structure, rec_chain:str, res_list:list[str]) -> list[str]: +def get_single_gaps(st: Structure, rec_chain: str, res_list: list[str]) -> list[str]: """ Get residues that are not in a list of residues but are between two residues which are in the list. From 5dcc01cc8bd83de8654053cf4e2a5668f55d805b Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 17:13:52 +0000 Subject: [PATCH 022/117] isort --- biomolecules/pdb_pockets/biolip_extraction.py | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 11ec323..9d1e991 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -1,16 +1,17 @@ -import pandas as pd -import re +import glob import os import random -import subprocess -import glob +import re import shutil +import subprocess import sys -from schrodinger.structure import Structure, StructureReader, StructureWriter -from schrodinger.structutils import build, analyze -from schrodinger.protein.captermini import CapTermini -from schrodinger.application import prepwizard + +import pandas as pd from schrodinger.adapter import evaluate_smarts +from schrodinger.application import prepwizard +from schrodinger.protein.captermini import CapTermini +from schrodinger.structure import Structure, StructureReader, StructureWriter +from schrodinger.structutils import analyze, build SCHRO = "/opt/schrodinger2024-1" From adc3ebe78ccf9ce967f83d113bc10d52a055309b Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 17:30:40 +0000 Subject: [PATCH 023/117] missing docstring --- biomolecules/pdb_pockets/biolip_extraction.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 9d1e991..3820bcd 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -220,6 +220,19 @@ def missing_backbone_check(st: Structure): def get_prepped_protein( pdb_id: str, row: pd.Series, prep: bool = True ) -> tuple[Structure, str]: + """ + Obtain a structure of the protein suitable for atomistic calculations + + This requires correct hydrogens on ligands and protein residues, proper + accounting for charge, formation of any disulfide bonds or zero-order bonds + to metals. + + :param pdb_id: PDB name to be obtained + :param row: Series containing receptor and ligand information + :param prep: If False, preparation steps can be skipped and we only + download a PDB as is + :return: Prepared structure and its filename for subsequent clean-up + """ baseoutname = f"{pdb_id}_prepped.maegz" pdb_name = pdb_id chains = {row["receptor_chain"], row["ligand_chain"]} From 9abc9cf7e2eefd0a2e0c1d3e225d9af51c5d1974 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 5 Jun 2024 18:53:02 +0000 Subject: [PATCH 024/117] Schrodinger is Python 3.8 --- biomolecules/pdb_pockets/biolip_extraction.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 3820bcd..50a36dc 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -7,6 +7,7 @@ import sys import pandas as pd +from typing import Tuple, List from schrodinger.adapter import evaluate_smarts from schrodinger.application import prepwizard from schrodinger.protein.captermini import CapTermini @@ -171,7 +172,7 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id: str, chains: list[str]) -> str: +def download_cif(pdb_id: str, chains: List[str]) -> str: """ Download cif (as opposed to pdb) of a given protein and extract the needed chains. @@ -219,7 +220,7 @@ def missing_backbone_check(st: Structure): def get_prepped_protein( pdb_id: str, row: pd.Series, prep: bool = True -) -> tuple[Structure, str]: +) -> Tuple[Structure, str]: """ Obtain a structure of the protein suitable for atomistic calculations @@ -352,7 +353,7 @@ def deprotonate_phosphate_esters(st: Structure) -> None: st.deleteAtoms(H_ats) -def make_gaps_gly(st: Structure, row: pd.Series, gap_res: list[str]) -> None: +def make_gaps_gly(st: Structure, row: pd.Series, gap_res: List[str]) -> None: """ Turn gap residues into glycines @@ -386,7 +387,7 @@ def make_gaps_gly(st: Structure, row: pd.Series, gap_res: list[str]) -> None: build.mutate(st, res.getAlphaCarbon(), "GLY") -def get_atom_lists(st: Structure, row: pd.Series) -> tuple[list[int], list[int]]: +def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]]: """ Get the lists of ligand atoms and receptor atoms @@ -432,7 +433,7 @@ def get_atom_lists(st: Structure, row: pd.Series) -> tuple[list[int], list[int]] return lig_ats, res_ats -def get_single_gaps(st: Structure, rec_chain: str, res_list: list[str]) -> list[str]: +def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[str]: """ Get residues that are not in a list of residues but are between two residues which are in the list. From 8536dd721a86b7120ea80f3f62824d70b384c7a8 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 18:15:47 +0000 Subject: [PATCH 025/117] filter to minimal pockets --- biomolecules/pdb_pockets/biolip_extraction.py | 52 +++++++++++++++++++ 1 file changed, 52 insertions(+) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 50a36dc..d5bf1a1 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -62,6 +62,7 @@ def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: dtype=types, keep_default_na=False, ) + # Parse the ligand specification biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ "ligand_residue_number" ].str.split("~", expand=True) @@ -77,9 +78,24 @@ def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ ["ligand_residue_number", "ligand_residue_end"] ].astype(int) + + # Remove duplicate pockets: These are pockets with the same ligand binding + # to exactly the same residues (including numbering). We don't require the + # PDB IDs to also match as closely related proteins or structures may have + # conserved binding sites which are still duplicates of each other. biolip_df.drop_duplicates( subset=["ligand_id", "binding_site_residues_pdb"], inplace=True ) + # Remove duplicate pockets: These are pockets with the same ligand in + # the same structure, often on different copies of the same chain. Sometimes + # there are residues that are right at the edge of inclusion, and so the + # pockets may be "different" by inclusion of an additional, marginal residue. + # We opt for only the smallest of such binding sites since these indicate the + # key interactions. + biolip_df = biolip_df.groupby(['pdb_id', 'ligand_id'], group_keys=False)[biolip_df.columns].apply(get_minimal_pockets).sort_index() + + # Note whether this molecule is drug-like by checking if it has any + # binding informations biolip_df["has_binding_info"] = ( biolip_df[ [ @@ -98,6 +114,42 @@ def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: biolip_df = biolip_df[~biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] return biolip_df +def is_sublist(smaller:List, larger:List) -> bool: + """ + Determine if the smaller list is a (not necessarily contiguous) + sub-list of the larger list + + :param smaller: smaller list + :param larger: larger list + :return: True if smaller is ordered sublist of larger + """ + it = iter(larger) + return all(item in it for item in smaller) + +def get_minimal_pockets(group:pd.DataFrame) -> List[int]: + """ + Filter BioLiP entries by selecting the smallest set of residues that + bind a particular ligand in a particular protein. + + :param group: entries which share a pdb_id and ligand_id to filter + :return: locations of entries in the group which are minimal binding pockets + """ + group['residue_list'] = group['binding_site_residues_pdb'].apply(lambda x: x.split()) + subset_rows = [] + rows = [row for _, row in group.iterrows()] + rows.sort(key=lambda x:len(x['residue_list'])) + while len(rows) > 1: + subset_rows.append(rows[0]) + idx_to_delete = [] + for idx, row in enumerate(list(rows[1:]),1): + if is_sublist(rows[0]['residue_list'], row['residue_list']): + idx_to_delete.append(idx) + for idx in reversed(idx_to_delete): + del rows[idx] + rows = rows[1:] + subset_rows.extend(rows) + group.drop(columns=['residue_list'], inplace=True) + return group.loc[[row.name for row in subset_rows]] def retreive_ligand_and_env( biolip_df: pd.DataFrame, From a2807021187e5527dc33cb1650d84ead62cd5fe2 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 18:35:37 +0000 Subject: [PATCH 026/117] make more efficient/pythonic --- biomolecules/pdb_pockets/biolip_extraction.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index d5bf1a1..9d4a325 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -140,13 +140,7 @@ def get_minimal_pockets(group:pd.DataFrame) -> List[int]: rows.sort(key=lambda x:len(x['residue_list'])) while len(rows) > 1: subset_rows.append(rows[0]) - idx_to_delete = [] - for idx, row in enumerate(list(rows[1:]),1): - if is_sublist(rows[0]['residue_list'], row['residue_list']): - idx_to_delete.append(idx) - for idx in reversed(idx_to_delete): - del rows[idx] - rows = rows[1:] + rows = [row for row in rows[1:] if not is_ordered_subset(rows[0]['residue_list'], row['residue_list'])] subset_rows.extend(rows) group.drop(columns=['residue_list'], inplace=True) return group.loc[[row.name for row in subset_rows]] From 7edbc071ef9a35e6eb787a179128dba36edcd214 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 18:36:17 +0000 Subject: [PATCH 027/117] black --- biomolecules/pdb_pockets/biolip_extraction.py | 27 ++++++++++++++----- 1 file changed, 20 insertions(+), 7 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 9d4a325..d75d457 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -92,7 +92,11 @@ def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: # pockets may be "different" by inclusion of an additional, marginal residue. # We opt for only the smallest of such binding sites since these indicate the # key interactions. - biolip_df = biolip_df.groupby(['pdb_id', 'ligand_id'], group_keys=False)[biolip_df.columns].apply(get_minimal_pockets).sort_index() + biolip_df = ( + biolip_df.groupby(["pdb_id", "ligand_id"], group_keys=False)[biolip_df.columns] + .apply(get_minimal_pockets) + .sort_index() + ) # Note whether this molecule is drug-like by checking if it has any # binding informations @@ -114,7 +118,8 @@ def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: biolip_df = biolip_df[~biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] return biolip_df -def is_sublist(smaller:List, larger:List) -> bool: + +def is_sublist(smaller: List, larger: List) -> bool: """ Determine if the smaller list is a (not necessarily contiguous) sub-list of the larger list @@ -126,7 +131,8 @@ def is_sublist(smaller:List, larger:List) -> bool: it = iter(larger) return all(item in it for item in smaller) -def get_minimal_pockets(group:pd.DataFrame) -> List[int]: + +def get_minimal_pockets(group: pd.DataFrame) -> List[int]: """ Filter BioLiP entries by selecting the smallest set of residues that bind a particular ligand in a particular protein. @@ -134,17 +140,24 @@ def get_minimal_pockets(group:pd.DataFrame) -> List[int]: :param group: entries which share a pdb_id and ligand_id to filter :return: locations of entries in the group which are minimal binding pockets """ - group['residue_list'] = group['binding_site_residues_pdb'].apply(lambda x: x.split()) + group["residue_list"] = group["binding_site_residues_pdb"].apply( + lambda x: x.split() + ) subset_rows = [] rows = [row for _, row in group.iterrows()] - rows.sort(key=lambda x:len(x['residue_list'])) + rows.sort(key=lambda x: len(x["residue_list"])) while len(rows) > 1: subset_rows.append(rows[0]) - rows = [row for row in rows[1:] if not is_ordered_subset(rows[0]['residue_list'], row['residue_list'])] + rows = [ + row + for row in rows[1:] + if not is_ordered_subset(rows[0]["residue_list"], row["residue_list"]) + ] subset_rows.extend(rows) - group.drop(columns=['residue_list'], inplace=True) + group.drop(columns=["residue_list"], inplace=True) return group.loc[[row.name for row in subset_rows]] + def retreive_ligand_and_env( biolip_df: pd.DataFrame, ligand_size_limit: int = 50, From ea015e72199958c495264b08c90d38162b5ba0b0 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 18:43:11 +0000 Subject: [PATCH 028/117] store biolip_df as pickle --- biomolecules/pdb_pockets/biolip_extraction.py | 165 +++++++++--------- 1 file changed, 86 insertions(+), 79 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index d75d457..9b501f8 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -30,87 +30,94 @@ class MissingResiduesError(Exception): def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: - columns = [ - "pdb_id", - "receptor_chain", - "resolution", - "binding_site_number_code", - "ligand_id", - "ligand_chain", - "ligand_serial_number", - "binding_site_residues_pdb", - "binding_site_residues_re-numbered", - "catalytic_site_residues_pdb", - "catalytic_site_residues_re-numbered", - "ec_number", - "go_terms", - "binding_affinity_manual", - "binding_affinity_binding_moad", - "binding_affinity_pdbbind_cn", - "binding_affinity_bindingdb", - "uniprot_ids", - "pubmed_id", - "ligand_residue_number", - "receptor_sequence", - ] - types = {col: str for col in columns} - types["ligand_serial_number"] = int - biolip_df = pd.read_csv( - "BioLiP_05_31_2024.txt", - sep="\t", - names=columns, - dtype=types, - keep_default_na=False, - ) - # Parse the ligand specification - biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ - "ligand_residue_number" - ].str.split("~", expand=True) - biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].fillna( - biolip_df["ligand_residue_number"] - ) - biolip_df[["ligand_residue_number", "ligand_residue_inscode"]] = biolip_df[ - "ligand_residue_number" - ].str.extract(r"(-?\d+)([A-Z\s]+)$") - biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].str.extract( - r"(-?\d+)" - ) - biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ - ["ligand_residue_number", "ligand_residue_end"] - ].astype(int) - - # Remove duplicate pockets: These are pockets with the same ligand binding - # to exactly the same residues (including numbering). We don't require the - # PDB IDs to also match as closely related proteins or structures may have - # conserved binding sites which are still duplicates of each other. - biolip_df.drop_duplicates( - subset=["ligand_id", "binding_site_residues_pdb"], inplace=True - ) - # Remove duplicate pockets: These are pockets with the same ligand in - # the same structure, often on different copies of the same chain. Sometimes - # there are residues that are right at the edge of inclusion, and so the - # pockets may be "different" by inclusion of an additional, marginal residue. - # We opt for only the smallest of such binding sites since these indicate the - # key interactions. - biolip_df = ( - biolip_df.groupby(["pdb_id", "ligand_id"], group_keys=False)[biolip_df.columns] - .apply(get_minimal_pockets) - .sort_index() - ) + pkl_name = "biolip_df.pkl" + if os.path.exists(pkl_name): + biolip_df = pd.read_pickle(pkl_name) + else: + columns = [ + "pdb_id", + "receptor_chain", + "resolution", + "binding_site_number_code", + "ligand_id", + "ligand_chain", + "ligand_serial_number", + "binding_site_residues_pdb", + "binding_site_residues_re-numbered", + "catalytic_site_residues_pdb", + "catalytic_site_residues_re-numbered", + "ec_number", + "go_terms", + "binding_affinity_manual", + "binding_affinity_binding_moad", + "binding_affinity_pdbbind_cn", + "binding_affinity_bindingdb", + "uniprot_ids", + "pubmed_id", + "ligand_residue_number", + "receptor_sequence", + ] + types = {col: str for col in columns} + types["ligand_serial_number"] = int + biolip_df = pd.read_csv( + "BioLiP_05_31_2024.txt", + sep="\t", + names=columns, + dtype=types, + keep_default_na=False, + ) + # Parse the ligand specification + biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ + "ligand_residue_number" + ].str.split("~", expand=True) + biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].fillna( + biolip_df["ligand_residue_number"] + ) + biolip_df[["ligand_residue_number", "ligand_residue_inscode"]] = biolip_df[ + "ligand_residue_number" + ].str.extract(r"(-?\d+)([A-Z\s]+)$") + biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].str.extract( + r"(-?\d+)" + ) + biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ + ["ligand_residue_number", "ligand_residue_end"] + ].astype(int) + + # Remove duplicate pockets: These are pockets with the same ligand binding + # to exactly the same residues (including numbering). We don't require the + # PDB IDs to also match as closely related proteins or structures may have + # conserved binding sites which are still duplicates of each other. + biolip_df.drop_duplicates( + subset=["ligand_id", "binding_site_residues_pdb"], inplace=True + ) + # Remove duplicate pockets: These are pockets with the same ligand in + # the same structure, often on different copies of the same chain. Sometimes + # there are residues that are right at the edge of inclusion, and so the + # pockets may be "different" by inclusion of an additional, marginal residue. + # We opt for only the smallest of such binding sites since these indicate the + # key interactions. + biolip_df = ( + biolip_df.groupby(["pdb_id", "ligand_id"], group_keys=False)[ + biolip_df.columns + ] + .apply(get_minimal_pockets) + .sort_index() + ) - # Note whether this molecule is drug-like by checking if it has any - # binding informations - biolip_df["has_binding_info"] = ( - biolip_df[ - [ - "binding_affinity_manual", - "binding_affinity_binding_moad", - "binding_affinity_pdbbind_cn", - "binding_affinity_bindingdb", + # Note whether this molecule is drug-like by checking if it has any + # binding informations + biolip_df["has_binding_info"] = ( + biolip_df[ + [ + "binding_affinity_manual", + "binding_affinity_binding_moad", + "binding_affinity_pdbbind_cn", + "binding_affinity_bindingdb", + ] ] - ] - != "" - ).any(axis=1) + != "" + ).any(axis=1) + biolip_df.to_pickle(pkl_name) if lig_type == "macromol": biolip_df = biolip_df[biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] From 7b800d6784ecc5dac9b6bc10a6b61c48fded15ef Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 19:01:46 +0000 Subject: [PATCH 029/117] cleanup --- biomolecules/pdb_pockets/biolip_extraction.py | 33 ++++++++++++++----- 1 file changed, 25 insertions(+), 8 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 9b501f8..74d5548 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -5,6 +5,7 @@ import shutil import subprocess import sys +import argparse import pandas as pd from typing import Tuple, List @@ -158,7 +159,7 @@ def get_minimal_pockets(group: pd.DataFrame) -> List[int]: rows = [ row for row in rows[1:] - if not is_ordered_subset(rows[0]["residue_list"], row["residue_list"]) + if not is_sublist(rows[0]["residue_list"], row["residue_list"]) ] subset_rows.extend(rows) group.drop(columns=["residue_list"], inplace=True) @@ -170,6 +171,7 @@ def retreive_ligand_and_env( ligand_size_limit: int = 50, start_pdb: int = 0, end_pdb: int = 1000, + output_path: str = '.' ) -> None: """ Extract ligand and its environment from BioLiP examples @@ -179,6 +181,12 @@ def retreive_ligand_and_env( 2) Obtain list of atoms which are assigned as ligands or receptors in BioLiP 3) Extract the receptor residues and cap them to match the source protein 4) Write the extracted structure to a pdb file + + :param biolip_df: Dataframe storing BioLiP database + :param ligand_size_limit: largest ligand size to extract from BioLiP + :param start_pdb: index of first pdb to run in the dataframe + :param end_pdb: index of last pdb to run in dataframe + :param output_path: where to store results """ # random.seed(12341) grouped_biolip = biolip_df.groupby("pdb_id") @@ -230,7 +238,7 @@ def retreive_ligand_and_env( print(e) continue ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) - fname = f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb" + fname = os.path.join(output_path, f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb") ligand_env.write(fname) # Cleanup the remaining prepped files for this pdb_id @@ -484,19 +492,22 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] continue lig_ats.extend(res.getAtomIndices()) # Add in coordinating groups for ions + coord_ats = [] if len(lig_ats) == 1: asl_str = f"fillres within 3 atom.num {lig_ats[0]}" - coord_ats = analyze.evaluate_asl(st, asl_str) - lig_ats.extend([at for at in coord_ats if at not in res_ats]) + coord_ats = [at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats] # mark the ligand chain for at in lig_ats: st.atom[at].chain = "l" + # mark the coord chain + for at in coord_ats: + st.atom[at].chain = "c" # mark the receptor chain for at in res_ats: st.atom[at].chain = "A" - return lig_ats, res_ats + return lig_ats + coord_ats, res_ats def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[str]: @@ -551,12 +562,18 @@ def cap_termini(st: Structure, ligand_env: Structure) -> None: pass +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument('--start_idx', type=int,required=True) + parser.add_argument('--end_idx', type=int, required=True) + parser.add_argument("--output_path", default='.') + return parser.parse_args() + def main(): + args = parse_args() biolip_df = get_biolip_db() - start_pdb = int(sys.argv[1]) - end_pdb = int(sys.argv[2]) ligand_env = retreive_ligand_and_env( - biolip_df, start_pdb=start_pdb, end_pdb=end_pdb + biolip_df, start_pdb=args.start_idx, end_pdb=args.end_idx, output_path=args.output_path ) From 68fa23c83568040a5ad9ad301caecbed795bbd2f Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 6 Jun 2024 19:02:08 +0000 Subject: [PATCH 030/117] black --- biomolecules/pdb_pockets/biolip_extraction.py | 23 +++++++++++++------ 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 74d5548..71c39df 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -171,7 +171,7 @@ def retreive_ligand_and_env( ligand_size_limit: int = 50, start_pdb: int = 0, end_pdb: int = 1000, - output_path: str = '.' + output_path: str = ".", ) -> None: """ Extract ligand and its environment from BioLiP examples @@ -238,7 +238,10 @@ def retreive_ligand_and_env( print(e) continue ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) - fname = os.path.join(output_path, f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb") + fname = os.path.join( + output_path, + f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb", + ) ligand_env.write(fname) # Cleanup the remaining prepped files for this pdb_id @@ -495,7 +498,9 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] coord_ats = [] if len(lig_ats) == 1: asl_str = f"fillres within 3 atom.num {lig_ats[0]}" - coord_ats = [at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats] + coord_ats = [ + at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats + ] # mark the ligand chain for at in lig_ats: @@ -564,16 +569,20 @@ def cap_termini(st: Structure, ligand_env: Structure) -> None: def parse_args(): parser = argparse.ArgumentParser() - parser.add_argument('--start_idx', type=int,required=True) - parser.add_argument('--end_idx', type=int, required=True) - parser.add_argument("--output_path", default='.') + parser.add_argument("--start_idx", type=int, required=True) + parser.add_argument("--end_idx", type=int, required=True) + parser.add_argument("--output_path", default=".") return parser.parse_args() + def main(): args = parse_args() biolip_df = get_biolip_db() ligand_env = retreive_ligand_and_env( - biolip_df, start_pdb=args.start_idx, end_pdb=args.end_idx, output_path=args.output_path + biolip_df, + start_pdb=args.start_idx, + end_pdb=args.end_idx, + output_path=args.output_path, ) From d46a50643ab42bc9a96267604ce4c1f63d36f92e Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 12 Jun 2024 22:37:10 +0000 Subject: [PATCH 031/117] use FAIR cluster Schrodinger --- biomolecules/pdb_pockets/biolip_extraction.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 71c39df..3e6016b 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -15,7 +15,7 @@ from schrodinger.structure import Structure, StructureReader, StructureWriter from schrodinger.structutils import analyze, build -SCHRO = "/opt/schrodinger2024-1" +SCHRO = "/private/home/levineds/schrodinger2024-2" class OnlyCAError(Exception): @@ -30,8 +30,8 @@ class MissingResiduesError(Exception): pass -def get_biolip_db(lig_type: str = "reg") -> pd.DataFrame: - pkl_name = "biolip_df.pkl" +def get_biolip_db(lig_type: str = "reg", pklpath:str = '.') -> pd.DataFrame: + pkl_name = os.path.join(pklpath, "biolip_df.pkl") if os.path.exists(pkl_name): biolip_df = pd.read_pickle(pkl_name) else: @@ -577,7 +577,7 @@ def parse_args(): def main(): args = parse_args() - biolip_df = get_biolip_db() + biolip_df = get_biolip_db(pklpath=args.output_path) ligand_env = retreive_ligand_and_env( biolip_df, start_pdb=args.start_idx, From 4c5603eb1852e4e74eeea997b0bbbf921517b3b7 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 12 Jun 2024 22:55:51 +0000 Subject: [PATCH 032/117] disable ligand size limit --- biomolecules/pdb_pockets/biolip_extraction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 3e6016b..b55f52d 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -168,7 +168,7 @@ def get_minimal_pockets(group: pd.DataFrame) -> List[int]: def retreive_ligand_and_env( biolip_df: pd.DataFrame, - ligand_size_limit: int = 50, + ligand_size_limit: int = 250, start_pdb: int = 0, end_pdb: int = 1000, output_path: str = ".", From d8525623331ceb9ff1578c1a0daac4541c3e97a9 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 03:40:45 +0000 Subject: [PATCH 033/117] move error message --- biomolecules/pdb_pockets/biolip_extraction.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index b55f52d..5888944 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -196,9 +196,9 @@ def retreive_ligand_and_env( pdb_id = pdb_list[pdb_count] rows = grouped_biolip.get_group(pdb_id) print(f"preparing {pdb_id} (entry: {pdb_count})") - sys.stdout.flush() prepped_pdb_fnames = set() for idx, row in rows.iterrows(): + sys.stdout.flush() binding_site_counter = ( row["binding_site_number_code"] + row["receptor_chain"] ) @@ -365,6 +365,7 @@ def get_prepped_protein( os.remove(file_to_del) for deldir in glob.glob(f"{basename}-???"): shutil.rmtree(deldir) + sys.stdout.flush() return st, outname @@ -397,6 +398,7 @@ def run_prepwizard(fname: str, outname: str) -> None: ) except subprocess.TimeoutExpired as e: # Try again without PROPKA (which seems to be where things get stuck) + print("PrepWizard is taking too long, try without PROPKA") subprocess.run( [ os.path.join(SCHRO, "utilities", "prepwizard"), @@ -490,7 +492,7 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] res_name = f'{row["ligand_chain"]}:{res_num}{row["ligand_residue_inscode"]}' try: res = st.findResidue(res_name) - except MissingResiduesError: + except ValueError: print(f"missing expected residue: {res_name}") continue lig_ats.extend(res.getAtomIndices()) From ce26492826cf100e28e7f3f2e173134bd5b3023a Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 03:58:58 +0000 Subject: [PATCH 034/117] alternate multiprocessing --- metal-organics/mprun.py | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/metal-organics/mprun.py b/metal-organics/mprun.py index 89e1498..9b0bd08 100644 --- a/metal-organics/mprun.py +++ b/metal-organics/mprun.py @@ -1,14 +1,15 @@ """ Adapted from Architector/development/lig_sampling/production_scripts/mpirun.py """ import argparse +import multiprocessing as mp import os import pathlib import pickle import subprocess import sys import time -from concurrent.futures import ProcessPoolExecutor, as_completed from datetime import datetime +from functools import partial import pandas as pd from tqdm import tqdm @@ -84,7 +85,6 @@ def parse_args(): def main(): args = parse_args() - n_workers = args.n_workers batch_idx = args.batch_idx if not os.path.exists(args.outpath): os.mkdir(args.outpath) @@ -106,15 +106,12 @@ def main(): inp_dict["name"] = str(i) newindf_rows.append(inp_dict) - with ProcessPoolExecutor(max_workers=n_workers) as exe: - futs = [] - for d in newindf_rows[batch_idx * args.batch_size : (batch_idx + 1) * args.batch_size]: - # print('Submitting: {}'.format(i)) - fut = exe.submit(calc, d, args.outpath) - futs.append(fut) - # Track progress of completed jobs. - for x in tqdm(as_completed(futs), total=len(futs)): - res = x.result() + pool = mp.Pool(args.n_workers) + fxn = partial(calc, outpath=args.outpath) + batch = newindf_rows[ + batch_idx * args.batch_size : (batch_idx + 1) * args.batch_size + ] + list(tqdm(pool.imap(fxn, batch), total=len(batch))) if __name__ == "__main__": From 923168ca997cfb00227f8bf746b3fdf680f59675 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 22:27:28 +0000 Subject: [PATCH 035/117] correct cif outname error --- biomolecules/pdb_pockets/biolip_extraction.py | 26 +++++++++++++------ 1 file changed, 18 insertions(+), 8 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 5888944..509bae6 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -219,6 +219,10 @@ def retreive_ligand_and_env( except MissingAtomsError: print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") continue + except MissingResiduesError: + print(f"Error on {pdb_id}, BS{binding_site_counter}: Ligand residue is missing") + continue + # Count heavy atoms of ligand and skip if too large heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] @@ -249,7 +253,7 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id: str, chains: List[str]) -> str: +def download_cif(pdb_id: str, chains: List[str]) -> Tuple[str, str]: """ Download cif (as opposed to pdb) of a given protein and extract the needed chains. @@ -268,9 +272,10 @@ def download_cif(pdb_id: str, chains: List[str]) -> str: at_list.extend(st.chain[chain].getAtomList()) st = st.extract(at_list) fname = f"{pdb_id}.maegz" + outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" with StructureWriter(fname) as writer: writer.append(st) - return fname + return fname, outname def missing_backbone_check(st: Structure): @@ -337,7 +342,8 @@ def get_prepped_protein( subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_name]) if not os.path.exists(fname): # PDB could not be downloaded, try the cif - fname = download_cif(pdb_id, chains) + fname, outname = download_cif(pdb_id, chains) + st = StructureReader.read(fname) # Reject structure that are just a bunch of CA missing_backbone_check(st) @@ -348,10 +354,14 @@ def get_prepped_protein( st.write(fname) # Run PrepWizard - try: - run_prepwizard(fname, outname) - except subprocess.TimeoutExpired: - raise RuntimeError("PrepWizard took longer than 2 hours, skipping") + if not os.path.exists(outname): + # We have to check for outname existence again because the proper outname + # for PDBs that have to be downloaded as CIFs isn't known until after + # we download them and can see their chain names. + try: + run_prepwizard(fname, outname) + except subprocess.TimeoutExpired: + raise RuntimeError("PrepWizard took longer than 2 hours, skipping") if not os.path.exists(outname): raise RuntimeError("PrepWizard failed") @@ -494,7 +504,7 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] res = st.findResidue(res_name) except ValueError: print(f"missing expected residue: {res_name}") - continue + raise MissingResiduesError lig_ats.extend(res.getAtomIndices()) # Add in coordinating groups for ions coord_ats = [] From c460cb7ba4cbe55b8928572524d04035a2bea8ad Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 22:44:32 +0000 Subject: [PATCH 036/117] try multiple times to download if needed --- biomolecules/pdb_pockets/biolip_extraction.py | 20 +++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 509bae6..33cdc2f 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -6,6 +6,7 @@ import subprocess import sys import argparse +import time import pandas as pd from typing import Tuple, List @@ -211,6 +212,8 @@ def retreive_ligand_and_env( print(f"Error on {pdb_id}: PrepWizard failed") print(e) continue + except ConnectionError: + print(f"Error on {pdb_id}: Could not reach PDB server, try again later?") else: prepped_pdb_fnames.add(fname) @@ -262,10 +265,19 @@ def download_cif(pdb_id: str, chains: List[str]) -> Tuple[str, str]: :param chains: list of relevant chain names to extract :return: filename where structure has been downloaded """ - subprocess.run( - [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] - ) - st = StructureReader.read(f"{pdb_id}.cif") + cif_name = f"{pdb_id}.cif" + for i in range(3): + subprocess.run( + [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] + ) + if os.path.exists(cif_name): + break + else: + time.sleep(10) + else: + raise ConnectionError + + st = StructureReader.read(cif_name) # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours at_list = [] for chain in chains: From a26d9bb253fd0747a8cafd37fc07dfe24e6418a1 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 22:49:14 +0000 Subject: [PATCH 037/117] formatting --- biomolecules/pdb_pockets/biolip_extraction.py | 27 ++++++++++--------- 1 file changed, 14 insertions(+), 13 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 33cdc2f..c2a3a8b 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -1,17 +1,15 @@ +import argparse import glob import os import random -import re import shutil import subprocess import sys -import argparse import time +from typing import List, Tuple import pandas as pd -from typing import Tuple, List from schrodinger.adapter import evaluate_smarts -from schrodinger.application import prepwizard from schrodinger.protein.captermini import CapTermini from schrodinger.structure import Structure, StructureReader, StructureWriter from schrodinger.structutils import analyze, build @@ -31,7 +29,7 @@ class MissingResiduesError(Exception): pass -def get_biolip_db(lig_type: str = "reg", pklpath:str = '.') -> pd.DataFrame: +def get_biolip_db(lig_type: str = "reg", pklpath: str = ".") -> pd.DataFrame: pkl_name = os.path.join(pklpath, "biolip_df.pkl") if os.path.exists(pkl_name): biolip_df = pd.read_pickle(pkl_name) @@ -213,7 +211,9 @@ def retreive_ligand_and_env( print(e) continue except ConnectionError: - print(f"Error on {pdb_id}: Could not reach PDB server, try again later?") + print( + f"Error on {pdb_id}: Could not reach PDB server, try again later?" + ) else: prepped_pdb_fnames.add(fname) @@ -223,9 +223,10 @@ def retreive_ligand_and_env( print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") continue except MissingResiduesError: - print(f"Error on {pdb_id}, BS{binding_site_counter}: Ligand residue is missing") + print( + f"Error on {pdb_id}, BS{binding_site_counter}: Ligand residue is missing" + ) continue - # Count heavy atoms of ligand and skip if too large heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] @@ -355,7 +356,7 @@ def get_prepped_protein( if not os.path.exists(fname): # PDB could not be downloaded, try the cif fname, outname = download_cif(pdb_id, chains) - + st = StructureReader.read(fname) # Reject structure that are just a bunch of CA missing_backbone_check(st) @@ -418,7 +419,7 @@ def run_prepwizard(fname: str, outname: str) -> None: ], timeout=3600 * 2, # Wait not more than 2 hours ) - except subprocess.TimeoutExpired as e: + except subprocess.TimeoutExpired: # Try again without PROPKA (which seems to be where things get stuck) print("PrepWizard is taking too long, try without PROPKA") subprocess.run( @@ -476,8 +477,8 @@ def make_gaps_gly(st: Structure, row: pd.Series, gap_res: List[str]) -> None: """ for res_num in gap_res: res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') - ## You have to be pretty weird to not be a Standard Residue, - ## just keep these as is + # You have to be pretty weird to not be a Standard Residue, + # just keep these as is if not res.isStandardResidue(): continue # If the residue being turned to GLY is not just a simple amino @@ -602,7 +603,7 @@ def parse_args(): def main(): args = parse_args() biolip_df = get_biolip_db(pklpath=args.output_path) - ligand_env = retreive_ligand_and_env( + retreive_ligand_and_env( biolip_df, start_pdb=args.start_idx, end_pdb=args.end_idx, From 42536c37d5d85ef2a7852d87c66d134188a2e943 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 23:28:07 +0000 Subject: [PATCH 038/117] change for smaller sampling --- metal-organics/architector_sampling.py | 23 +++++++++++++---------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/metal-organics/architector_sampling.py b/metal-organics/architector_sampling.py index 28192c3..1738b70 100644 --- a/metal-organics/architector_sampling.py +++ b/metal-organics/architector_sampling.py @@ -2,15 +2,16 @@ import argparse from typing import Optional +from tqdm import tqdm import architector.io_ptable as io_ptable import mendeleev import numpy as np import pandas as pd -MAX_N_ATOMS = 250 +MAX_N_ATOMS = 120 # Set seed -random_seed = 46139 +random_seed = 98745 np.random.seed(random_seed) @@ -205,14 +206,16 @@ def create_sample( history_uids = [] total = 0 out_rows = [] - while total < nsamples: - sample_row, uid = sample( - metal_df=metal_df, ligands_df=ligands_df, test=test, maxCN=maxCN - ) - if uid not in history_uids: - total += 1 - history_uids.append(uid) - out_rows.append(sample_row) + with tqdm(total=nsamples) as pbar: + while total < nsamples: + sample_row, uid = sample( + metal_df=metal_df, ligands_df=ligands_df, test=test, maxCN=maxCN + ) + if uid not in history_uids: + total += 1 + history_uids.append(uid) + out_rows.append(sample_row) + pbar.update(1) dfout = pd.DataFrame(out_rows) return dfout, history_uids From bad07e7269ed2e41a7f544dff8553c939264f5b5 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 14 Jun 2024 23:40:51 +0000 Subject: [PATCH 039/117] add error checking around mutation --- biomolecules/pdb_pockets/biolip_extraction.py | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index c2a3a8b..836f908 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -29,6 +29,10 @@ class MissingResiduesError(Exception): pass +class MutateError(Exception): + pass + + def get_biolip_db(lig_type: str = "reg", pklpath: str = ".") -> pd.DataFrame: pkl_name = os.path.join(pklpath, "biolip_df.pkl") if os.path.exists(pkl_name): @@ -227,6 +231,12 @@ def retreive_ligand_and_env( f"Error on {pdb_id}, BS{binding_site_counter}: Ligand residue is missing" ) continue + except MutateError: + print( + f"Error on {pdb_id}, BS{binding_site_counter}: Cannot mutate gap residue to GLY" + ) + continue + # Count heavy atoms of ligand and skip if too large heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] @@ -485,8 +495,13 @@ def make_gaps_gly(st: Structure, row: pd.Series, gap_res: List[str]) -> None: # acid, e.g. it is bound to a ligand, it can't be mutated properly # and it will actually also garble the structure if res.getBetaCarbon() is not None: + if res.getAlphaCarbon() is None: + raise MutateError st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) - build.mutate(st, res.getAlphaCarbon(), "GLY") + try: + build.mutate(st, res.getAlphaCarbon(), "GLY") + except: + raise MutateError def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]]: From 2e72c499add0c7e1615e5b0801a0bac35de13698 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Sat, 15 Jun 2024 04:29:01 +0000 Subject: [PATCH 040/117] protection for SMARTS evaluation --- biomolecules/pdb_pockets/biolip_extraction.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 836f908..0b96fad 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -457,7 +457,10 @@ def deprotonate_phosphate_esters(st: Structure) -> None: :param st: Structure with phosphate groups that can be deprotonated """ phos_smarts = "[*;!#1][*][P](=[O])([O])([O][H])" - matched_ats = evaluate_smarts(st, phos_smarts) + try: + matched_ats = evaluate_smarts(st, phos_smarts) + except ValueError: + matched_ats = [] H_ats = {ats[-1] for ats in matched_ats} O_ats = {ats[-2] for ats in matched_ats} for O_at in O_ats: From 901567beddc1305de911eb29506f2b3d62613dee Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Sat, 15 Jun 2024 05:32:29 +0000 Subject: [PATCH 041/117] BioLiP errors --- biomolecules/pdb_pockets/biolip_extraction.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 0b96fad..b1375b4 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -218,6 +218,10 @@ def retreive_ligand_and_env( print( f"Error on {pdb_id}: Could not reach PDB server, try again later?" ) + continue + except ValueError: + print(f"Error on {pdb_id}: BioLiP chain error") + continue else: prepped_pdb_fnames.add(fname) @@ -367,7 +371,9 @@ def get_prepped_protein( # PDB could not be downloaded, try the cif fname, outname = download_cif(pdb_id, chains) - st = StructureReader.read(fname) + st = next(StructureReader(fname), None) + if st is None: + raise ValueError # Reject structure that are just a bunch of CA missing_backbone_check(st) From db182860f80c5470501faa54aa8ae018f3c3455c Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 17 Jun 2024 21:50:27 +0000 Subject: [PATCH 042/117] remove duplicate "BS" --- biomolecules/pdb_pockets/biolip_extraction.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index b1375b4..9daf5c9 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -228,16 +228,16 @@ def retreive_ligand_and_env( try: lig_ats, res_ats = get_atom_lists(st, row) except MissingAtomsError: - print(f"Error on {pdb_id}, BS{binding_site_counter}: Atoms are missing") + print(f"Error on {pdb_id}, {binding_site_counter}: Atoms are missing") continue except MissingResiduesError: print( - f"Error on {pdb_id}, BS{binding_site_counter}: Ligand residue is missing" + f"Error on {pdb_id}, {binding_site_counter}: Ligand residue is missing" ) continue except MutateError: print( - f"Error on {pdb_id}, BS{binding_site_counter}: Cannot mutate gap residue to GLY" + f"Error on {pdb_id}, {binding_site_counter}: Cannot mutate gap residue to GLY" ) continue @@ -255,7 +255,7 @@ def retreive_ligand_and_env( cap_termini(st, ligand_env) except Exception as e: print( - f"Error on {pdb_id}, BS{binding_site_counter}: Cannot cap termini" + f"Error on {pdb_id}, {binding_site_counter}: Cannot cap termini" ) print(e) continue From 8c2e2e6df6227962c90ad6b8010e76391cd41ebd Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 18 Jun 2024 22:05:36 +0000 Subject: [PATCH 043/117] add timeout to architector structure generation --- metal-organics/mprun.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/metal-organics/mprun.py b/metal-organics/mprun.py index 9b0bd08..5a9b484 100644 --- a/metal-organics/mprun.py +++ b/metal-organics/mprun.py @@ -37,9 +37,9 @@ def calc(input_dict: dict, outpath: str) -> bool: try: subprocess.check_output( ["python", "generate_structures.py", pickle_input, outpath], - universal_newlines=True, + universal_newlines=True, timeout=3600*12 ) - except subprocess.CalledProcessError as e: + except (subprocess.CalledProcessError, subprocess.TimeoutExpired) as e: end = time.time() with open( os.path.join(outpath, input_dict["name"] + "_failed.txt"), "w" From cdfbb0261cbf386361c1782dfac867aa8595fe80 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 18 Jun 2024 22:05:56 +0000 Subject: [PATCH 044/117] formatting --- metal-organics/architector_sampling.py | 4 ++-- metal-organics/generate_structures.py | 1 - 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/metal-organics/architector_sampling.py b/metal-organics/architector_sampling.py index 1738b70..6884fbc 100644 --- a/metal-organics/architector_sampling.py +++ b/metal-organics/architector_sampling.py @@ -2,12 +2,12 @@ import argparse from typing import Optional -from tqdm import tqdm import architector.io_ptable as io_ptable import mendeleev import numpy as np import pandas as pd +from tqdm import tqdm MAX_N_ATOMS = 120 # Set seed @@ -249,7 +249,7 @@ def main(): metal_df = pd.read_pickle("metal_sample_dataframe.pkl") ligands_df = pd.read_pickle("ligand_sample_dataframe.pkl") if args.history is not None: - with open(args.history, 'r') as fh: + with open(args.history, "r") as fh: history = eval(fh.read()) else: history = None diff --git a/metal-organics/generate_structures.py b/metal-organics/generate_structures.py index a1e0f65..407a520 100644 --- a/metal-organics/generate_structures.py +++ b/metal-organics/generate_structures.py @@ -6,7 +6,6 @@ import time import pandas as pd - # import datetime from architector import build_complex From f36e4508c468dd5a05dd06fcdbcced99e9647ee6 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 18 Jun 2024 22:06:19 +0000 Subject: [PATCH 045/117] improve xyz generation --- metal-organics/analyze_outputs.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/metal-organics/analyze_outputs.py b/metal-organics/analyze_outputs.py index 5fd07e2..253172e 100644 --- a/metal-organics/analyze_outputs.py +++ b/metal-organics/analyze_outputs.py @@ -4,6 +4,7 @@ import pandas as pd from architector import convert_io_molecule +from tqdm import tqdm def parse_args(): @@ -15,8 +16,10 @@ def parse_args(): def main(): args = parse_args() path = pathlib.Path(args.output_path) - for fname in path.glob("*.pkl"): - name = os.path.join("xyzs", os.path.splitext(os.path.basename(fname))[0]) + xyz_path = path / "xyzs" + xyz_path.mkdir(exist_ok=True) + for fname in tqdm(path.glob("*.pkl"), total=len(list(path.glob("*.pkl")))): + name = xyz_path / os.path.splitext(os.path.basename(fname))[0] df = pd.read_pickle(fname) for i, row in df.iterrows(): mol = convert_io_molecule(row["mol2string"]) From 46df04099daa1174a4794a0efb2b775cca2b6cdd Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 20 Jun 2024 21:53:53 +0000 Subject: [PATCH 046/117] add slightly more error checking --- biomolecules/pdb_pockets/biolip_extraction.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 9daf5c9..da05640 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -267,6 +267,7 @@ def retreive_ligand_and_env( ligand_env.write(fname) # Cleanup the remaining prepped files for this pdb_id + print('done with', pdb_count, pdb_id) for fname in prepped_pdb_fnames: os.remove(fname) @@ -540,7 +541,7 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] try: res = st.findResidue(res_name) except ValueError: - print(f"missing expected residue: {res_name}") + print(f"missing expected ligand residue: {res_name}") raise MissingResiduesError lig_ats.extend(res.getAtomIndices()) # Add in coordinating groups for ions @@ -583,7 +584,11 @@ def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[ parent_indices = set() parent_list = list(st.chain[rec_chain].residue) for res_name in res_list: - res = st.findResidue(f"{rec_chain}:{res_name}") + try: + res = st.findResidue(f"{rec_chain}:{res_name}") + except ValueError: + print(f"missing expected receptor residue: {rec_chain}:{res_name}") + raise MissingResiduesError parent_indices.add(parent_list.index(res)) gaps = [ val + 1 From 301c199d6e54325a1a40e4e9cf2cfde7499207a0 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 25 Jun 2024 05:24:56 +0000 Subject: [PATCH 047/117] more fixes --- biomolecules/pdb_pockets/biolip_extraction.py | 87 +++++++++++-------- 1 file changed, 52 insertions(+), 35 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index da05640..1f34b1a 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -175,6 +175,7 @@ def retreive_ligand_and_env( start_pdb: int = 0, end_pdb: int = 1000, output_path: str = ".", + fill_sidechain: bool = True, ) -> None: """ Extract ligand and its environment from BioLiP examples @@ -190,6 +191,7 @@ def retreive_ligand_and_env( :param start_pdb: index of first pdb to run in the dataframe :param end_pdb: index of last pdb to run in dataframe :param output_path: where to store results + :param fill_sidechain: If True, PrepWizard will try and fill in missing side chains """ # random.seed(12341) grouped_biolip = biolip_df.groupby("pdb_id") @@ -206,7 +208,7 @@ def retreive_ligand_and_env( row["binding_site_number_code"] + row["receptor_chain"] ) try: - st, fname = get_prepped_protein(pdb_id, row) + st, fname = get_prepped_protein(pdb_id, row, fill_sidechain) except OnlyCAError: print(f"Error on {pdb_id}: Structure has only CA") continue @@ -230,9 +232,9 @@ def retreive_ligand_and_env( except MissingAtomsError: print(f"Error on {pdb_id}, {binding_site_counter}: Atoms are missing") continue - except MissingResiduesError: + except MissingResiduesError as e: print( - f"Error on {pdb_id}, {binding_site_counter}: Ligand residue is missing" + f"Error on {pdb_id}, {binding_site_counter}: {e} residue is missing" ) continue except MutateError: @@ -241,7 +243,6 @@ def retreive_ligand_and_env( ) continue - # Count heavy atoms of ligand and skip if too large heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] if len(heavy_lig_ats) > ligand_size_limit: @@ -254,9 +255,7 @@ def retreive_ligand_and_env( try: cap_termini(st, ligand_env) except Exception as e: - print( - f"Error on {pdb_id}, {binding_site_counter}: Cannot cap termini" - ) + print(f"Error on {pdb_id}, {binding_site_counter}: Cannot cap termini") print(e) continue ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) @@ -267,7 +266,7 @@ def retreive_ligand_and_env( ligand_env.write(fname) # Cleanup the remaining prepped files for this pdb_id - print('done with', pdb_count, pdb_id) + print("done with", pdb_count, pdb_id) for fname in prepped_pdb_fnames: os.remove(fname) @@ -329,7 +328,7 @@ def missing_backbone_check(st: Structure): def get_prepped_protein( - pdb_id: str, row: pd.Series, prep: bool = True + pdb_id: str, row: pd.Series, fill_sidechain: bool = True, prep: bool = True ) -> Tuple[Structure, str]: """ Obtain a structure of the protein suitable for atomistic calculations @@ -340,6 +339,9 @@ def get_prepped_protein( :param pdb_id: PDB name to be obtained :param row: Series containing receptor and ligand information + :param fill_sidechain: If True, PrepWizard will try and fill in missing + side chains. Note, this can actually delete covalently + attached ligands. :param prep: If False, preparation steps can be skipped and we only download a PDB as is :return: Prepared structure and its filename for subsequent clean-up @@ -376,7 +378,7 @@ def get_prepped_protein( if st is None: raise ValueError # Reject structure that are just a bunch of CA - missing_backbone_check(st) + # missing_backbone_check(st) # Remove any dummy atoms, PrepWizard doesn't like them dummy_atoms = [at for at in st.atom if at.atomic_number < 1] @@ -389,13 +391,14 @@ def get_prepped_protein( # for PDBs that have to be downloaded as CIFs isn't known until after # we download them and can see their chain names. try: - run_prepwizard(fname, outname) + run_prepwizard(fname, outname, fill_sidechain) except subprocess.TimeoutExpired: raise RuntimeError("PrepWizard took longer than 2 hours, skipping") if not os.path.exists(outname): raise RuntimeError("PrepWizard failed") st = StructureReader.read(outname) + remove_alternate_positions(st) deprotonate_phosphate_esters(st) st = build.reorder_protein_atoms_by_sequence(st) @@ -409,7 +412,7 @@ def get_prepped_protein( return st, outname -def run_prepwizard(fname: str, outname: str) -> None: +def run_prepwizard(fname: str, outname: str, fill_sidechain: bool) -> None: """ Run Schrodinger's PrepWizard @@ -421,40 +424,50 @@ def run_prepwizard(fname: str, outname: str) -> None: :param fname: input file name for PrepWizard :param outname: output file name from PrepWizard + :param fill_sidechain: If True, try to fill in side chains """ + args = [ + os.path.join(SCHRO, "utilities", "prepwizard"), + fname, + outname, + "-noepik", + "-noimpref", + "-disulfides", + "-NOJOBID", + ] + if fill_sidechain: + args.append("-fillsidechains") try: subprocess.run( - [ - os.path.join(SCHRO, "utilities", "prepwizard"), - fname, - outname, - "-noepik", - "-noimpref", - "-fillsidechains", - "-disulfides", - "-NOJOBID", - ], + args, timeout=3600 * 2, # Wait not more than 2 hours ) except subprocess.TimeoutExpired: # Try again without PROPKA (which seems to be where things get stuck) print("PrepWizard is taking too long, try without PROPKA") + args.append("-nopropka") subprocess.run( - [ - os.path.join(SCHRO, "utilities", "prepwizard"), - fname, - outname, - "-noepik", - "-noimpref", - "-fillsidechains", - "-disulfides", - "-nopropka", - "-NOJOBID", - ], + args, timeout=3600 * 2, # Wait not more than 2 hours ) +def remove_alternate_positions(st): + """ + Some PDBs have alternate positions for some atoms, we only want the main one + + :param st: Structure which may have alternate positions + """ + alt_coord_names = ["_pdb_alt_", "_m_alt_", "s_pdb_altloc_chars"] + alt_props = [ + prop + for prop in st.getAtomPropertyNames() + if any(alt_prop in prop for alt_prop in alt_coord_names) + ] + for prop in alt_props: + st.deletePropertyFromAllAtoms(prop) + + def deprotonate_phosphate_esters(st: Structure) -> None: """ At physiological pH, it's a good assumption that any phosphate esters @@ -542,7 +555,7 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] res = st.findResidue(res_name) except ValueError: print(f"missing expected ligand residue: {res_name}") - raise MissingResiduesError + raise MissingResiduesError("Ligand") lig_ats.extend(res.getAtomIndices()) # Add in coordinating groups for ions coord_ats = [] @@ -588,7 +601,7 @@ def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[ res = st.findResidue(f"{rec_chain}:{res_name}") except ValueError: print(f"missing expected receptor residue: {rec_chain}:{res_name}") - raise MissingResiduesError + raise MissingResiduesError("Receptor") parent_indices.add(parent_list.index(res)) gaps = [ val + 1 @@ -626,6 +639,9 @@ def parse_args(): parser.add_argument("--start_idx", type=int, required=True) parser.add_argument("--end_idx", type=int, required=True) parser.add_argument("--output_path", default=".") + parser.add_argument( + "--no_fill_sidechain", dest="fill_sidechain", action="store_false" + ) return parser.parse_args() @@ -637,6 +653,7 @@ def main(): start_pdb=args.start_idx, end_pdb=args.end_idx, output_path=args.output_path, + fill_sidechain=args.fill_sidechain, ) From b56de8d038b140d92f2015f49c4476d2a59af663 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 26 Jun 2024 23:59:44 +0000 Subject: [PATCH 048/117] function already exists of course --- biomolecules/pdb_pockets/biolip_extraction.py | 19 ++----------------- 1 file changed, 2 insertions(+), 17 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 1f34b1a..5ef7e45 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -196,6 +196,7 @@ def retreive_ligand_and_env( # random.seed(12341) grouped_biolip = biolip_df.groupby("pdb_id") pdb_list = list(grouped_biolip.groups.keys()) + pdb_list = ['1a0q'] for pdb_count in range(start_pdb, end_pdb): # pdb_id = random.choice(list(grouped_biolip.groups.keys())) pdb_id = pdb_list[pdb_count] @@ -398,7 +399,7 @@ def get_prepped_protein( raise RuntimeError("PrepWizard failed") st = StructureReader.read(outname) - remove_alternate_positions(st) + st = build.remove_alternate_positions(st) deprotonate_phosphate_esters(st) st = build.reorder_protein_atoms_by_sequence(st) @@ -452,22 +453,6 @@ def run_prepwizard(fname: str, outname: str, fill_sidechain: bool) -> None: ) -def remove_alternate_positions(st): - """ - Some PDBs have alternate positions for some atoms, we only want the main one - - :param st: Structure which may have alternate positions - """ - alt_coord_names = ["_pdb_alt_", "_m_alt_", "s_pdb_altloc_chars"] - alt_props = [ - prop - for prop in st.getAtomPropertyNames() - if any(alt_prop in prop for alt_prop in alt_coord_names) - ] - for prop in alt_props: - st.deletePropertyFromAllAtoms(prop) - - def deprotonate_phosphate_esters(st: Structure) -> None: """ At physiological pH, it's a good assumption that any phosphate esters From 30ed02c230e5a236bd33487c2b31c091f768dbf0 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Thu, 27 Jun 2024 10:00:25 -0700 Subject: [PATCH 049/117] trying to handle multi-atom solutes, committing before migrating to schrodinger --- electrolytes/README.md | 57 + electrolytes/run_extraction.sh | 18 +- electrolytes/solvation_shell_extract.py | 190 +- .../{Al_Cl04 => Al_ClO4}/system.data | 0 electrolytes/testfiles/LiPF6/system.data | 41220 ++++++++++++++++ electrolytes/utils.py | 13 + 6 files changed, 41426 insertions(+), 72 deletions(-) rename electrolytes/testfiles/{Al_Cl04 => Al_ClO4}/system.data (100%) create mode 100644 electrolytes/testfiles/LiPF6/system.data create mode 100644 electrolytes/utils.py diff --git a/electrolytes/README.md b/electrolytes/README.md index e69de29..5d5a445 100644 --- a/electrolytes/README.md +++ b/electrolytes/README.md @@ -0,0 +1,57 @@ +List of questions as of 5/30: + +1. Do we want to remove the other solutes (including counterion on the same solute) when doing the solvation analysis? +2. How to handle multiple solutes or solvents with the same atoms present? Can't just select by atom names + One Idea: Pass in a list of lists of solutes and solvents - how to automatically get this from the PDB or LAMMPS file? +3. How do we want to deal with coordination numbers? I.e. pick a defined min and max as we're doing currently, or pick the k most common coordination numbers? Or pick a set number from each type of coordination number? Over-sample the rare ones? +4. For the case of multiple solvents, not enough to split up shells by coordination number - need to also split up by number of each solvent. +5. What to do when it's only an ionic liquid (no solvent) + + +Notes from chatting with Evan: + +Maybe put ionic liquids on hold + +Focus on the case where we have one or more solutes and one or more solvents + +Compute average solvation radius over all atoms in the solute (or randomly sample a subset for larger solute molecules) + +Anything that isn't the solute under consideration needs to be defined as a separate solvent (with some cutoff to ensure that we don't have silly comparison e.g between two cations.) + +Save rdfs and rdf data/troughs, etc so that if needed, we can do a post-analysis with tabulaed radii + +For solvent-solvent interactions, try two approaches: +1. Same analysis code as with solutes, but just make the solvent a solute (may not work if there aren't clear RDFs for the solvent) +2. Pick random solvent molecules, pick a random radius with bounds determined by a solvent-dependent heuristic, sample shells, sort by composition, and pick most diverse + + + +Meeting on 6/7: + +Main problem with the current analysis pipeline is that there are different analysis approaches for low concentration, high concentration, ionic liquids, etc. Also unclear how to define radii for multi-atom solutes. This is going to be too slow. + +Maybe the simplest approach is to choose 2-3 heuristic radii (not system specific) around each solute and solvent and then bin them by composition/graph hash. + +How do we determine these radii? Go through a few sample pdb files with different cases (multi solute, multi solvent, ionic liquid, etc.) and then do some heuristic solvation analysis to find the radii. + +Question: when we expand a shell around a solute, if we run into another solute, do we also expand around that? Probably not needed because this will be captured in the next larger radius. + +Schrodinger has easy ways to do this. Sanjeev/Daniel sit down and work with Schrodinger to see if it solves all these problems. + +LAMMPS files from Muhammad need to have a mapping from atom to residue names and solute/solvent. Muhammad and Evan work on this together + + +Meeting of 6/11 with Daniel: +MGCF at Berkeley +Maestro for visualizing stuff + +Schrodinger easily accounts for different atom orderings (e.g permutations, etc.) and PBCs + + + + + + + + + diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index b2c10c7..7f555db 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -5,15 +5,23 @@ # python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ # --save_dir 'results' \ # --system_name 'Al_ClO4' \ -# --solute_atoms 'AL0' \ +# --solute_atoms 'C' \ # --min_coord 2 \ # --max_coord 5 \ # --top_n 20 -python solvation_shell_extract.py --input_dir 'testfiles/NaCl' \ +# python solvation_shell_extract.py --input_dir 'testfiles/LiPF6' \ +# --save_dir 'results' \ +# --system_name 'LiPF6' \ +# --solute_atoms 'P00' 'F01' 'F02' 'F03' 'F04' 'F05' 'F06' \ +# --min_coord 2 \ +# --max_coord 20 \ +# --top_n 20 + +python solvation_shell_extract.py --input_dir 'testfiles/Al_ClO4' \ --save_dir 'results' \ - --system_name 'NaCl' \ - --solute_atoms 'NA0' \ + --system_name 'Al_ClO4' \ + --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ --min_coord 2 \ - --max_coord 5 \ + --max_coord 20 \ --top_n 20 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 144e85e..7c8e986 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -4,6 +4,7 @@ import random import numpy as np from tqdm import tqdm +from typing import List from collections import defaultdict import matplotlib.pyplot as plt import MDAnalysis as mda @@ -15,13 +16,15 @@ wrap_positions, extract_charges_from_lammps_file, ) +from utils import parse_list_of_lists def extract_solvation_shells( input_dir: str, save_dir: str, system_name: str, - solute_atoms: str, + solute_atoms: List[str], + solvent_atoms: List[List[str]], min_coord: int, max_coord: int, top_n: int, @@ -32,12 +35,13 @@ def extract_solvation_shells( extract and save the top_n most diverse snapshots based on a RMSD criterion. Args: - pdb_file_path: Path to the PDB file containing the MD trajectory - save_dir: Directory in which to save extracted solvation shells - system_name: Name of the system - used for naming the save directory - solute_atom: Name (in the PDB file) of the solute atom type (e.g NA0) with which to perform the solvation analysis - min_coord: Minimum coordination number to consider - max_coord: Maximum coordination number to consider + input_dir: Path to 1) the PDB file containing the MD trajectory and 2) the LAMMPS file containing the initial structure (used to extract partial charges). + save_dir: Directory in which to save extracted solvation shells. + system_name: Name of the system - used for naming the save directory. + solute_atoms: List of names (in the PDB file) of the solute atom types (e.g NA0) with which to perform the solvation analysis. + solvent_atoms: List of names (in the PDB file) of the solvent atom types with which to perform the solvation analysis. + min_coord: Minimum coordination number to consider. + max_coord: Maximum coordination number to consider. top_n: Number of snapshots to extract per coordination number. """ solute_atoms_name = " ".join(solute_atoms) @@ -64,93 +68,138 @@ def extract_solvation_shells( # Choose solute atom # TODO: try to join multiple atoms in the same solute, doesn't currently work - query = " or ".join(f"name {atom}" for atom in solute_atoms) - solu = universe.select_atoms(query) + solute_query = " or ".join(f"name {atom}" for atom in solute_atoms) + solute = universe.select_atoms(solute_query) + # other_query = " or ".join(f"name {atom}" for atom in other_solute_atoms) + # other_solu = universe.select_atoms(other_query) logging.info("Translating atoms to solute center of mass") for ts in tqdm(universe.trajectory): ts.dimensions = universe.dimensions - solu_center = solu.center_of_mass(wrap=True) + solu_center = solute.center_of_mass(wrap=True) dim = ts.triclinic_dimensions box_center = np.sum(dim, axis=0) / 2 universe.atoms.translate(box_center - solu_center) universe.atoms.unwrap() - solvent = universe.atoms - solu + # TODO: need to remove the other components of the solute from the solvent atoms? Doesn't matter since the other solute atom won't be close? - solv_anal = Solute.from_atoms(solu, {"solvent": solvent}) + # This doesn't handle multiple solvents + solvent = ( + universe.atoms - solute + ) # TODO: might need to count anything other than the solute of interest as a potential solvent + # TODO: set an upper cutoff for solute-solvent interactions + + solute_name = "".join(atom for atom in solute_atoms) - # Identify the cutoff for the first solvation shell, based on the MD trajectory logging.info("Running solvation analysis") + # Identify the cutoff for the first solvation shell, based on the MD trajectory + + # discovered that the reason the analysis was failing was because the default cutoff region of 6.5 was too small for the Cl04 anion + kernel_kwargs = {"cutoff_region": (1.5, 8)} + solv_anal = Solute.from_atoms( + solute, + {"solvent": solvent}, + solute_name=solute_name, + kernel_kwargs=kernel_kwargs, + ) + # TODO: subsample fewer solutes to speed up the analysis + + solv_anal.run() # which solute's radii is this using? + + max_radii = 0 + max_name = "" + for solute_name in solv_anal.atom_solutes.keys(): + radii = solv_anal.atom_solutes[solute_name].radii["solvent"] + if radii > max_radii: + max_radii = radii + max_name = solute_name + + # TODO: what do we do with this max or mean radii? Can we need to use it to re-run the analysis? - # this line fails (can't find the radius) - solv_anal.run() + # except AssertionError: + # logging.info("Failed to automatically find the radius, trying again with a heuristic radius") + # heuristic_radii = 2.5 # TODO: add heuristic radii based on effective sizes of solute and solvent + # solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name = solute_name, radii={'solvent': heuristic_radii}) + # solv_anal.run() # Plot the RDF - solv_anal.plot_solvation_radius("solute", "solvent") + solv_anal.plot_solvation_radius(max_name, "solvent") plt.savefig( os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png") ) # There's probably a much faster way to do this # But for now, we're prototyping, so slow is okay + + # Store the solvation shells with different numbers of solvents (sorted from highest to lowest frequency) shells = dict() for j in solv_anal.speciation.speciation_fraction["solvent"]: shells[j] = solv_anal.speciation.get_shells({"solvent": j}) # Now let's try getting the most diverse structures for each particular coordination number # This is also a bit slow, particularly for the more common and/or larger solvent shells + + # TODO: instead of specifying a range of coordination numbers, we could specify the top n most common coordination numbers (but we also probably want to extract rare configurations) for c in range(min_coord, max_coord + 1): - logging.info(f"Processing shells with coordination number {c}") - os.makedirs( - os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), - exist_ok=True, - ) - shell_species = [] - shell_positions = [] - for index, _ in tqdm(shells[c].iterrows()): - ts = universe.trajectory[index[0]] - universe.atoms.unwrap() - shell = solv_anal.solvation_data.xs( - (index[0], index[1]), level=(FRAME, SOLUTE_IX) + if c in shells.keys(): + logging.info( + f"Processing {len(shells[c])} shells with coordination number {c}" ) - shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) - shell = shell.copy() - if len(shell.atoms.elements) > len(shell_species): - shell_species = shell.atoms.elements - - shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) - - by_num_atoms = defaultdict(list) - for sps in shell_positions: - by_num_atoms[len(sps)].append(sps) - - # filter by number of atoms per shell - selections_by_num_atoms = { - num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) - for num_atoms, shells_with_num_atoms in by_num_atoms.items() - } - - for ( - shell_size, - shell_positions, - ) in selections_by_num_atoms.items(): # loop over sizes - for idx, shell_pos in enumerate(shell_positions): - if shell_pos.shape[0] == shell_species.shape[0]: - - # Save shell as xyz file - mol = Molecule(shell_species, shell_pos, charge=round(sum(charges))) - mol.to( - os.path.join( - save_dir, - system_name, - solute_atoms_name, - f"coord={c}", - f"size{shell_size}_selection{idx}.xyz", - ), - "xyz", - ) + os.makedirs( + os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), + exist_ok=True, + ) + shell_species = [] + shell_positions = [] + # Extract the shell positions + + for i, (index, _) in tqdm(enumerate(shells[c].iterrows())): + universe.atoms.unwrap() + frame, solute_idx = index + shell = solv_anal.solvation_data.xs( + (frame, solute_idx), level=(FRAME, SOLUTE_IX) + ) + shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) + # TODO: assertion that compositions/element orderings are the same + if len(shell.atoms.elements) > len(shell_species): + shell_species = shell.atoms.elements + shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) + if i > 1000: # TODO: don't hardcode this + break + + by_num_atoms = defaultdict(list) + for sps in shell_positions: + by_num_atoms[len(sps)].append(sps) + + # filter by number of atoms per shell + selections_by_num_atoms = { + num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) + for num_atoms, shells_with_num_atoms in by_num_atoms.items() + } + + for ( + shell_size, + shell_positions, + ) in selections_by_num_atoms.items(): # loop over sizes + for idx, shell_pos in enumerate(shell_positions): + if shell_pos.shape[0] == shell_species.shape[0]: + + # Save shell as xyz file + mol = Molecule( + shell_species, shell_pos, charge=round(sum(charges)) + ) + mol.to( + os.path.join( + save_dir, + system_name, + solute_atoms_name, + f"coord={c}", + f"size{shell_size}_selection{idx}.xyz", + ), + "xyz", + ) if __name__ == "__main__": @@ -169,10 +218,16 @@ def extract_solvation_shells( ) parser.add_argument( "--solute_atoms", - type=str, - nargs="+", - help="Which solute atom(s) to extract solvation shells for (accepts multiple values)", + type=parse_list_of_lists, + help="Which solute atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", ) + + parser.add_argument( + "--solvent_atoms", + type=parse_list_of_lists, + help="Which solvent atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", + ) + parser.add_argument( "--min_coord", type=int, help="Minimum shell coordination number to extract" ) @@ -193,6 +248,7 @@ def extract_solvation_shells( args.save_dir, args.system_name, args.solute_atoms, + args.solvent_atoms, args.min_coord, args.max_coord, args.top_n, diff --git a/electrolytes/testfiles/Al_Cl04/system.data b/electrolytes/testfiles/Al_ClO4/system.data similarity index 100% rename from electrolytes/testfiles/Al_Cl04/system.data rename to electrolytes/testfiles/Al_ClO4/system.data diff --git a/electrolytes/testfiles/LiPF6/system.data b/electrolytes/testfiles/LiPF6/system.data new file mode 100644 index 0000000..cf3d649 --- /dev/null +++ b/electrolytes/testfiles/LiPF6/system.data @@ -0,0 +1,41220 @@ +LAMMPS Description + + 8198 atoms + 7486 bonds + 12772 angles + 9500 dihedrals + 3200 impropers + + 28 atom types + 25 bond types + 41 angle types + 38 dihedral types + 12 improper types + + -25.0 25.0 xlo xhi + -25.0 25.0 ylo yhi + -25.0 25.0 zlo zhi + +Masses + +1 6.94 # Li +2 30.974 # P +3 18.998 # F +4 12.011 # type1_c_unk_6dedc +5 12.011 # type2_c_unk_6dedc +6 15.999 # type3_o_unk_6dedc +7 12.011 # type4_c_unk_6dedc +8 15.999 # type5_o_unk_6dedc +9 15.999 # type6_o_unk_6dedc +10 1.008 # type7_h_unk_6dedc +11 1.008 # type8_h_unk_6dedc +12 1.008 # type9_h_unk_6dedc +13 1.008 # type10_h_unk_6dedc +14 12.011 # type1_c_unk_29441 +15 12.011 # type2_c_unk_29441 +16 15.999 # type3_o_unk_29441 +17 12.011 # type4_c_unk_29441 +18 15.999 # type5_o_unk_29441 +19 15.999 # type6_o_unk_29441 +20 12.011 # type7_c_unk_29441 +21 1.008 # type8_h_unk_29441 +22 1.008 # type9_h_unk_29441 +23 1.008 # type10_h_unk_29441 +24 1.008 # type11_h_unk_29441 +25 1.008 # type12_h_unk_29441 +26 1.008 # type13_h_unk_29441 +27 1.008 # type14_h_unk_29441 +28 1.008 # type15_h_unk_29441 + +Atoms # full + +1 1 1 1 -17.112 1.014 -10.684 +2 2 1 1 16.744 23.352 24.34 +3 3 1 1 16.354 -14.783 -22.587 +4 4 1 1 3.629 -17.789 8.111 +5 5 1 1 16.114 -11.644 22.39 +6 6 1 1 20.111 -5.014 10.978 +7 7 1 1 -24.872 21.712 10.467 +8 8 1 1 7.803 -18.98 11.202 +9 9 1 1 11.752 10.282 -10.223 +10 10 1 1 -20.568 -24.505 -12.628 +11 11 1 1 -4.766 12.416 9.784 +12 12 1 1 17.947 12.452 -12.752 +13 13 1 1 3.916 16.302 18.558 +14 14 1 1 -5.182 -8.247 20.824 +15 15 1 1 -9.895 9.552 -5.628 +16 16 1 1 -8.533 -24.503 -11.294 +17 17 1 1 15.222 16.523 10.679 +18 18 1 1 -18.019 -15.761 10.995 +19 19 1 1 -9.99 18.096 -19.117 +20 20 1 1 5.772 -21.091 -24.202 +21 21 1 1 12.356 -16.602 6.19 +22 22 1 1 -24.067 18.82 12.723 +23 23 1 1 16.572 -9.874 23.712 +24 24 1 1 -21.152 -18.543 0.425 +25 25 1 1 -21.419 -4.667 -6.187 +26 26 1 1 10.303 -5.172 -8.962 +27 27 1 1 -1.564 -16.437 15.776 +28 28 1 1 19.63 -1.072 21.626 +29 29 1 1 11.72 -18.152 1.625 +30 30 1 1 5.459 -4.437 5.955 +31 31 1 1 10.856 -10.262 -10.499 +32 32 1 1 -21.278 7.527 -9.654 +33 33 1 1 -1.718 11.312 18.874 +34 34 1 1 -6.572 -10.772 -6.861 +35 35 1 1 18.922 0.083 -21.528 +36 36 1 1 3.904 18.376 8.467 +37 37 1 1 22.861 11.3 24.169 +38 38 1 1 -14.191 -0.011 6.245 +39 39 1 1 -0.564 1.813 -12.566 +40 40 1 1 -24.495 8.619 8.739 +41 41 1 1 -2.134 20.555 6.462 +42 42 1 1 22.467 0.598 14.89 +43 43 1 1 -0.453 -4.061 8.706 +44 44 1 1 -6.201 -16.74 12.732 +45 45 1 1 -16.975 -21.913 -17.218 +46 46 1 1 14.444 -11.627 9.513 +47 47 1 1 5.082 21.954 7.41 +48 48 1 1 -4.349 -1.467 4.101 +49 49 1 1 -11.006 -19.906 23.792 +50 50 1 1 -4.693 16.592 16.777 +51 51 1 1 -18.242 10.701 23.417 +52 52 1 1 23.311 3.825 -7.514 +53 53 1 1 6.428 -13.215 7.679 +54 54 1 1 -24.918 -13.061 -8.023 +55 55 1 1 -11.26 -24.291 -13.228 +56 56 1 1 1.39 2.436 12.466 +57 57 1 1 24.195 6.707 -13.011 +58 58 1 1 -7.521 -23.034 -23.882 +59 59 1 1 -14.238 -6.94 2.437 +60 60 1 1 0.36 11.705 -1.895 +61 61 1 1 -11.458 -19.188 2.481 +62 62 1 1 22.846 21.454 0.892 +63 63 1 1 0.255 12.413 6.27 +64 64 1 1 21.787 22.177 -23.606 +65 65 1 1 -10.861 13.191 24.178 +66 66 1 1 -20.064 -8.625 7.204 +67 67 1 1 18.495 -20.945 19.86 +68 68 1 1 16.281 -2.404 -1.818 +69 69 1 1 8.048 19.285 -9.741 +70 70 1 1 24.098 23.818 -18.659 +71 71 1 1 12.557 23.839 -23.154 +72 72 1 1 -19.089 23.341 -2.119 +73 73 1 1 1.873 23.648 16.543 +74 74 1 1 16.234 14.768 -8.269 +75 75 1 1 6.513 9.844 21.162 +76 76 1 1 0.75 -20.676 15.765 +77 77 1 1 6.707 6.653 -8.208 +78 78 1 1 -23.723 4.35 7.531 +79 79 1 1 -11.21 11.302 4.221 +80 80 1 1 1.587 14.887 -9.068 +81 81 1 1 23.804 -9.764 2.622 +82 82 1 1 16.726 7.861 3.757 +83 83 1 1 0.44 21.031 -1.111 +84 84 1 1 4.144 4.32 -2.76 +85 85 1 1 -7.27 8.297 14.339 +86 86 1 1 21.533 -8.131 -19.667 +87 87 1 1 -5.159 3.018 -5.377 +88 88 1 1 -7.032 -16.792 22.109 +89 89 1 1 -22.768 23.315 12.743 +90 90 1 1 -9.642 17.461 -9.179 +91 91 1 1 19.349 -16.521 15.217 +92 92 1 1 -3.626 5.284 -23.581 +93 93 1 1 0.754 13.909 -12.583 +94 94 1 1 -11.341 -17.185 12.48 +95 95 1 1 -10.569 -15.024 1.671 +96 96 1 1 -6.37 5.004 7.493 +97 97 1 1 11.267 15.065 3.847 +98 98 1 1 0.346 22.835 -21.278 +99 99 1 1 -10.124 10.864 14.347 +100 100 1 1 -3.039 -3.915 -12.96 +101 101 1 1 3.746 -24.533 9.947 +102 102 1 1 -5.856 -12.923 -5.537 +103 103 1 1 -2.008 1.509 -22.576 +104 104 1 1 8.023 -0.742 16.48 +105 105 1 1 -18.962 -21.831 -6.124 +106 106 1 1 -25.0 1.913 12.018 +107 107 1 1 15.447 21.115 -18.002 +108 108 1 1 -23.411 16.248 -15.411 +109 109 1 1 -4.724 -2.555 11.294 +110 110 1 1 -19.625 13.062 -12.803 +111 111 1 1 -12.668 13.0 -22.559 +112 112 1 1 4.766 -5.473 -0.018 +113 113 1 1 -7.376 0.795 -1.565 +114 114 1 1 7.137 23.827 -5.527 +115 115 1 1 9.282 -24.879 -10.418 +116 116 1 1 -15.975 -0.847 15.781 +117 117 1 1 18.677 11.548 21.399 +118 118 1 1 21.644 -7.535 14.277 +119 119 1 1 12.304 -3.937 1.2 +120 120 1 1 -11.603 1.509 24.146 +121 121 1 1 9.78 -4.681 4.208 +122 122 1 1 1.079 21.208 -14.939 +123 123 1 1 -9.971 11.437 -17.683 +124 124 1 1 22.999 5.206 23.712 +125 125 1 1 2.629 22.838 3.451 +126 126 1 1 21.062 11.307 9.071 +127 127 1 1 -10.06 -17.594 4.978 +128 128 1 1 6.068 0.35 19.198 +129 129 1 1 -2.402 17.533 -19.795 +130 130 1 1 5.33 -10.267 -22.915 +131 131 1 1 -3.917 -9.652 11.83 +132 132 1 1 -13.291 -16.192 0.235 +133 133 1 1 1.4 15.847 23.329 +134 134 1 1 -3.4 16.919 -11.531 +135 135 1 1 -16.201 -1.406 23.623 +136 136 1 1 -9.355 -14.576 -8.069 +137 137 1 1 -20.592 9.087 9.359 +138 138 1 1 -2.844 -24.798 -11.562 +139 139 1 1 -23.095 -23.628 11.891 +140 140 1 1 15.363 24.401 6.149 +141 141 1 1 5.802 13.068 -10.602 +142 142 1 1 18.497 15.692 11.458 +143 143 1 1 -17.777 11.04 -23.174 +144 144 1 1 23.379 -3.145 23.326 +145 145 1 1 -16.375 24.629 -1.64 +146 146 1 1 -16.236 -13.842 15.305 +147 147 1 1 11.664 0.903 15.142 +148 148 1 1 -3.429 8.328 24.384 +149 149 1 1 -13.757 -19.385 -16.301 +150 150 1 1 -21.481 9.075 -20.44 +151 151 1 1 4.203 -9.846 7.171 +152 152 1 1 1.737 21.156 -21.562 +153 153 1 1 10.832 7.422 7.982 +154 154 1 1 1.362 12.362 -14.154 +155 155 1 1 17.465 15.823 -14.586 +156 156 1 1 18.72 3.116 -22.511 +157 157 1 1 1.679 -16.667 -3.555 +158 158 1 1 7.364 18.669 2.96 +159 159 1 1 10.567 7.593 12.336 +160 160 1 1 14.461 -22.558 -23.673 +161 161 1 1 5.296 4.454 7.697 +162 162 1 1 -20.39 -1.66 -6.64 +163 163 1 1 24.348 15.587 3.332 +164 164 1 1 -3.391 9.365 -10.599 +165 165 1 1 22.919 -12.367 -2.7 +166 166 1 1 14.607 4.145 13.327 +167 167 1 1 -10.315 8.263 7.577 +168 168 1 1 -1.269 5.778 -0.582 +169 169 1 1 -7.373 1.882 -24.481 +170 170 1 1 20.539 -17.516 1.895 +171 171 1 1 21.132 -6.727 -13.529 +172 172 1 1 5.459 13.51 -21.528 +173 173 1 1 0.461 13.783 8.184 +174 174 1 1 -6.602 17.739 -4.186 +175 175 1 1 -11.241 -9.124 -18.783 +176 176 1 1 -23.641 1.844 16.246 +177 177 1 1 -20.48 -10.014 18.401 +178 178 1 1 20.73 2.209 -20.557 +179 179 1 1 -4.216 14.902 20.216 +180 180 1 1 3.474 6.837 6.083 +181 181 1 1 3.921 15.11 -21.742 +182 182 2 1.34 11.935 8.055 -20.842 +183 182 3 -0.39 12.784 7.235 -19.66 +184 182 3 -0.39 11.087 8.876 -22.023 +185 182 3 -0.39 11.082 8.873 -19.661 +186 182 3 -0.39 12.788 7.238 -22.022 +187 182 3 -0.39 13.093 9.258 -20.838 +188 182 3 -0.39 10.777 6.852 -20.845 +189 183 2 1.34 -2.872 9.564 -13.957 +190 183 3 -0.39 -2.292 10.704 -12.884 +191 183 3 -0.39 -3.453 8.423 -15.031 +192 183 3 -0.39 -3.623 8.761 -12.7 +193 183 3 -0.39 -2.122 10.366 -15.215 +194 183 3 -0.39 -4.247 10.483 -14.191 +195 183 3 -0.39 -1.498 8.644 -13.724 +196 184 2 1.34 12.695 10.591 10.282 +197 184 3 -0.39 11.37 11.583 10.058 +198 184 3 -0.39 14.021 9.6 10.506 +199 184 3 -0.39 13.183 10.889 8.712 +200 184 3 -0.39 12.208 10.294 11.851 +201 184 3 -0.39 13.587 11.902 10.807 +202 184 3 -0.39 11.804 9.281 9.756 +203 185 2 1.34 23.385 19.46 14.08 +204 185 3 -0.39 23.72 20.77 15.061 +205 185 3 -0.39 23.05 18.151 13.099 +206 185 3 -0.39 24.742 19.797 13.167 +207 185 3 -0.39 22.027 19.124 14.992 +208 185 3 -0.39 24.298 18.48 15.077 +209 185 3 -0.39 22.472 20.44 13.083 +210 186 2 1.34 14.219 -21.275 7.599 +211 186 3 -0.39 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+264 193 3 -0.39 -18.281 -24.239 -21.729 +265 193 3 -0.39 -16.209 -22.178 -20.113 +266 194 2 1.34 21.779 -4.089 5.727 +267 194 3 -0.39 22.121 -4.906 7.143 +268 194 3 -0.39 21.438 -3.271 4.311 +269 194 3 -0.39 23.246 -4.574 5.093 +270 194 3 -0.39 20.312 -3.603 6.361 +271 194 3 -0.39 21.058 -5.462 5.108 +272 194 3 -0.39 22.501 -2.716 6.346 +273 195 2 1.34 -3.37 -17.223 8.77 +274 195 3 -0.39 -1.911 -17.17 9.581 +275 195 3 -0.39 -4.829 -17.276 7.959 +276 195 3 -0.39 -3.126 -18.841 8.437 +277 195 3 -0.39 -3.614 -15.605 9.104 +278 195 3 -0.39 -4.145 -17.633 10.192 +279 195 3 -0.39 -2.595 -16.813 7.349 +280 196 2 1.34 22.803 -14.524 -5.516 +281 196 3 -0.39 21.535 -15.611 -5.551 +282 196 3 -0.39 24.071 -13.437 -5.48 +283 196 3 -0.39 23.619 -15.511 -4.443 +284 196 3 -0.39 21.987 -13.537 -6.588 +285 196 3 -0.39 23.522 -15.321 -6.795 +286 196 3 -0.39 22.085 -13.727 -4.236 +287 197 2 1.34 12.281 -23.749 14.76 +288 197 3 -0.39 10.989 -22.928 15.429 +289 197 3 -0.39 13.572 -24.569 14.09 +290 197 3 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Error: {e}" + ) From 1c7fd1aa6e810fbbceb5d6a7a766088b9fb57c75 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 13:02:08 -0700 Subject: [PATCH 050/117] start schrodinger workflow --- .gitignore | 14 + electrolytes/example_for_sanjeev.py | 120 + electrolytes/run_extraction.sh | 25 +- electrolytes/solvation_shell_extract.py | 311 +- electrolytes/solvation_shell_extract_old.py | 255 + electrolytes/solvation_shell_utils.py | 153 +- electrolytes/testfiles/Al_ClO4/system.data | 41322 ------------------ electrolytes/testfiles/LiPF6/system.data | 41220 ----------------- electrolytes/testfiles/NaCl/system.data | 3036 -- electrolytes/utils.py | 13 - 10 files changed, 598 insertions(+), 85871 deletions(-) create mode 100644 electrolytes/example_for_sanjeev.py create mode 100644 electrolytes/solvation_shell_extract_old.py delete mode 100644 electrolytes/testfiles/Al_ClO4/system.data delete mode 100644 electrolytes/testfiles/LiPF6/system.data delete mode 100644 electrolytes/testfiles/NaCl/system.data delete mode 100644 electrolytes/utils.py diff --git a/.gitignore b/.gitignore index 264f1a8..c650265 100644 --- a/.gitignore +++ b/.gitignore @@ -112,3 +112,17 @@ Local # VS Code .vscode/ + +# testfiles +testfiles/ +testfiles_old/ +*mae + +# Schrodinger stuff +maestro_package/ + +# Jupyter Notebook +.ipynb_checkpoints/ +*ipynb + + diff --git a/electrolytes/example_for_sanjeev.py b/electrolytes/example_for_sanjeev.py new file mode 100644 index 0000000..cce420d --- /dev/null +++ b/electrolytes/example_for_sanjeev.py @@ -0,0 +1,120 @@ +from schrodinger.structure import StructureReader +from schrodinger.structutils import analyze +import json + +# Read a structure +st = StructureReader.read("thing.mae") + +# Read json metadat file +with open("thing.json") as f: + metadata = json.load(f) + +# Get a molecule number +res = next((res for res in st.residue if res.pdbres == "AAA "), None) +if res is None: + mol_num = 1 +else: + mol_num = res.molecule_number + +# Extract entire residues (can also say fillmol if you prefer) within 3 angstroms of molecule 1 +ats = set(analyze.evaluate_asl(st, f"fillres within 3 mol {mol_num}")) +mol_included = [mol_num] + + +def get_extra_solutes(st, ats, radius, res_names, mol_included): + """ + Gets the molecule numbers of solute molecules that are within the radius + and not already included. + """ + extras = [] + for at in ats: + if st.atom[at].molecule_number in mol_included: + continue + if any(res_name == st.atom[at].getResidue().pdbres for res_name in res_names): + extras.append(st.atom[at].molecule_number) + return extras + + +extras = get_extra_solutes(st, ats, 3, ["AAA ", "BBB "], mol_included) +while extras: + ats.update( + analyze.evaluate_asl( + st, f'fillres within 3 mol {",".join([str(i) for i in extras])}' + ) + ) + mol_included.extend(extras) + if len(ats) < 200: + extras = get_extra_solutes(st, ats, 3, ["AAA ", "BBB "], mol_included) + else: + break +st2 = st.extract(sorted(ats), copy_props=True) +st2.write("thing2.mae") + +# Now do a random water near the box edge, molecule 91 +# label the molecule so we can keep track +for at in st.molecule[91].atom: + at.property["i_m_label"] = 1 +ats = analyze.evaluate_asl(st, "fillres within 3 mol 91") +st2 = st.extract(ats, copy_props=True) +st2.write("thing3.mae") + +# Oh no! Our system is broken across the PBC boundary. Let's tell it to contract +# everthing to be centered on our molecule of interest (this will also handle if +# a molecule is split across a PBC) +from schrodinger.application.matsci import clusterstruct + +mol_ats = [at.index for at in st2.atom if at.property.pop("i_m_label", None) == 1] +clusterstruct.contract_structure2(st2, contract_on_atoms=mol_ats) +st2.write("thing3b.mae") + +# Suppose we have several structures and we want to group them by conformers +from schrodinger.comparison import are_conformers +from schrodinger.application.jaguar.utils import group_items + + +def get_env_of_mol(st, mol_idx, radius): + st_copy = st.copy() + for at in st_copy.molecule[mol_idx].atom: + at.property["i_m_label"] = 1 + ats = analyze.evaluate_asl(st_copy, f"fillres within {radius} mol {mol_idx}") + st2 = st_copy.extract(ats, copy_props=True) + mol_ats = [at.index for at in st2.atom if at.property.pop("i_m_label", None) == 1] + clusterstruct.contract_structure2(st2, contract_on_atoms=mol_ats) + return st2 + + +st_list = [get_env_of_mol(st, i, 3) for i in range(2, 100)] + +grouped_items = group_items(st_list, are_conformers) +# we now have lists of lists of structures where each list of structures are conformers of each other + +from schrodinger.comparison.atom_mapper import ConnectivityAtomMapper +from schrodinger.structutils import rmsd + + +def renumber_molecules_to_match(mol_list): + """ + Ensure that topologically equivalent sites are equivalently numbered + """ + mapper = ConnectivityAtomMapper(use_chirality=False) + atlist = range(1, mol_list[0].atom_total + 1) + renumbered_mols = [mol_list[0]] + for mol in mol_list[1:]: + _, r_mol = mapper.reorder_structures(mol_list[0], atlist, mol, atlist) + renumbered_mols.append(r_mol) + return renumbered_mols + + +# Now we have ensured that topologically related atoms are equivalently numbered (up to molecular symmetry) +grouped_items = [renumber_molecules_to_match(items) for items in grouped_items] + +# example grouping +group = grouped_items[1] +# Compare all atoms for RMSD (remember that Schrodinger atoms/molecules are 1-indexed +at_list = list(range(1, group[0].atom_total + 1)) +# Note that this function will translate/rotate all structures to align with the first one +# If this is not desired, run function on a copy, e.g. other.copy() +rmsds = [ + rmsd.superimpose(group[0], at_list, other, at_list, use_symmetry=True) + for other in group[1:] +] diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index 7f555db..fd2e72d 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -1,27 +1,8 @@ #!/bin/bash #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? -# Run these scripts from om-data/electrolytes -# python solvation_shell_extract.py --pdb_file_path 'testfiles/al_clo4_example.pdb' \ -# --save_dir 'results' \ -# --system_name 'Al_ClO4' \ -# --solute_atoms 'C' \ -# --min_coord 2 \ -# --max_coord 5 \ -# --top_n 20 -# python solvation_shell_extract.py --input_dir 'testfiles/LiPF6' \ -# --save_dir 'results' \ -# --system_name 'LiPF6' \ -# --solute_atoms 'P00' 'F01' 'F02' 'F03' 'F04' 'F05' 'F06' \ -# --min_coord 2 \ -# --max_coord 20 \ -# --top_n 20 - -python solvation_shell_extract.py --input_dir 'testfiles/Al_ClO4' \ +$SCHRODINGER/run python3 solvation_shell_extract.py --input_dir 'testfiles/1' \ --save_dir 'results' \ - --system_name 'Al_ClO4' \ - --solute_atoms 'CL1' 'O00' 'O02' 'O03' 'O04' \ - --min_coord 2 \ - --max_coord 20 \ - --top_n 20 \ No newline at end of file + --system_name 'Li_BF4' + \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 7c8e986..36a3c6e 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -1,205 +1,135 @@ -import os +from typing import List import logging -import argparse + +logging.basicConfig(level=logging.INFO) import random -import numpy as np +import os from tqdm import tqdm -from typing import List -from collections import defaultdict -import matplotlib.pyplot as plt -import MDAnalysis as mda -from solvation_analysis.solute import Solute -from solvation_analysis._column_names import FRAME, SOLUTE_IX -from pymatgen.core.structure import Molecule +import json +import argparse + +from schrodinger.structure import StructureReader +from schrodinger.structutils import analyze from solvation_shell_utils import ( + expand_shell, + renumber_molecules_to_match, filter_by_rmsd, - wrap_positions, - extract_charges_from_lammps_file, ) -from utils import parse_list_of_lists +from schrodinger.comparison import are_conformers +from schrodinger.application.jaguar.utils import group_with_comparison +from schrodinger.structutils import rmsd def extract_solvation_shells( input_dir: str, save_dir: str, system_name: str, - solute_atoms: List[str], - solvent_atoms: List[List[str]], - min_coord: int, - max_coord: int, + radii: List[float], top_n: int, ): """ Given a MD trajectory in a PDB file, perform a solvation analysis - on the specified solute to extract the first solvation shell. For each coordination number in the specified range, - extract and save the top_n most diverse snapshots based on a RMSD criterion. + on the specified solute to extract the first solvation shell. Args: input_dir: Path to 1) the PDB file containing the MD trajectory and 2) the LAMMPS file containing the initial structure (used to extract partial charges). save_dir: Directory in which to save extracted solvation shells. system_name: Name of the system - used for naming the save directory. - solute_atoms: List of names (in the PDB file) of the solute atom types (e.g NA0) with which to perform the solvation analysis. - solvent_atoms: List of names (in the PDB file) of the solvent atom types with which to perform the solvation analysis. - min_coord: Minimum coordination number to consider. - max_coord: Maximum coordination number to consider. - top_n: Number of snapshots to extract per coordination number. + radii: List of solvation shell radii to extract. + top_n: Number of snapshots to extract per topology. """ - solute_atoms_name = " ".join(solute_atoms) - # Create save directory - os.makedirs(os.path.join(save_dir, system_name, solute_atoms_name), exist_ok=True) - - # Read charges from LAMMPS file - lammps_file_path = os.path.join(input_dir, "system.data") - charges = extract_charges_from_lammps_file(lammps_file_path) - - # Initialize MDA Universe - pdb_file_path = os.path.join(input_dir, "system_output.pdb") - universe = mda.Universe(pdb_file_path) - - # Add PBC box - with open(pdb_file_path) as file: - dimension_lines = file.readlines()[1] - a = float(dimension_lines.split()[1]) - b = float(dimension_lines.split()[2]) - c = float(dimension_lines.split()[3]) - universe.dimensions = [a, b, c, 90, 90, 90] - - lattices = np.array([a, b, c])[None][None] - - # Choose solute atom - # TODO: try to join multiple atoms in the same solute, doesn't currently work - solute_query = " or ".join(f"name {atom}" for atom in solute_atoms) - solute = universe.select_atoms(solute_query) - # other_query = " or ".join(f"name {atom}" for atom in other_solute_atoms) - # other_solu = universe.select_atoms(other_query) - - logging.info("Translating atoms to solute center of mass") - for ts in tqdm(universe.trajectory): - ts.dimensions = universe.dimensions - solu_center = solute.center_of_mass(wrap=True) - dim = ts.triclinic_dimensions - box_center = np.sum(dim, axis=0) / 2 - universe.atoms.translate(box_center - solu_center) - - universe.atoms.unwrap() - - # TODO: need to remove the other components of the solute from the solvent atoms? Doesn't matter since the other solute atom won't be close? - - # This doesn't handle multiple solvents - solvent = ( - universe.atoms - solute - ) # TODO: might need to count anything other than the solute of interest as a potential solvent - # TODO: set an upper cutoff for solute-solvent interactions - - solute_name = "".join(atom for atom in solute_atoms) - - logging.info("Running solvation analysis") - # Identify the cutoff for the first solvation shell, based on the MD trajectory - - # discovered that the reason the analysis was failing was because the default cutoff region of 6.5 was too small for the Cl04 anion - kernel_kwargs = {"cutoff_region": (1.5, 8)} - solv_anal = Solute.from_atoms( - solute, - {"solvent": solvent}, - solute_name=solute_name, - kernel_kwargs=kernel_kwargs, - ) - # TODO: subsample fewer solutes to speed up the analysis - - solv_anal.run() # which solute's radii is this using? - - max_radii = 0 - max_name = "" - for solute_name in solv_anal.atom_solutes.keys(): - radii = solv_anal.atom_solutes[solute_name].radii["solvent"] - if radii > max_radii: - max_radii = radii - max_name = solute_name - - # TODO: what do we do with this max or mean radii? Can we need to use it to re-run the analysis? - - # except AssertionError: - # logging.info("Failed to automatically find the radius, trying again with a heuristic radius") - # heuristic_radii = 2.5 # TODO: add heuristic radii based on effective sizes of solute and solvent - # solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name = solute_name, radii={'solvent': heuristic_radii}) - # solv_anal.run() - - # Plot the RDF - solv_anal.plot_solvation_radius(max_name, "solvent") - plt.savefig( - os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png") - ) - # There's probably a much faster way to do this - # But for now, we're prototyping, so slow is okay - - # Store the solvation shells with different numbers of solvents (sorted from highest to lowest frequency) - shells = dict() - for j in solv_anal.speciation.speciation_fraction["solvent"]: - shells[j] = solv_anal.speciation.get_shells({"solvent": j}) - - # Now let's try getting the most diverse structures for each particular coordination number - # This is also a bit slow, particularly for the more common and/or larger solvent shells - - # TODO: instead of specifying a range of coordination numbers, we could specify the top n most common coordination numbers (but we also probably want to extract rare configurations) - for c in range(min_coord, max_coord + 1): - if c in shells.keys(): - logging.info( - f"Processing {len(shells[c])} shells with coordination number {c}" - ) - os.makedirs( - os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), - exist_ok=True, - ) - shell_species = [] - shell_positions = [] - # Extract the shell positions - - for i, (index, _) in tqdm(enumerate(shells[c].iterrows())): - universe.atoms.unwrap() - frame, solute_idx = index - shell = solv_anal.solvation_data.xs( - (frame, solute_idx), level=(FRAME, SOLUTE_IX) - ) - shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) - # TODO: assertion that compositions/element orderings are the same - if len(shell.atoms.elements) > len(shell_species): - shell_species = shell.atoms.elements - shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) - if i > 1000: # TODO: don't hardcode this - break - - by_num_atoms = defaultdict(list) - for sps in shell_positions: - by_num_atoms[len(sps)].append(sps) - - # filter by number of atoms per shell - selections_by_num_atoms = { - num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) - for num_atoms, shells_with_num_atoms in by_num_atoms.items() - } - - for ( - shell_size, - shell_positions, - ) in selections_by_num_atoms.items(): # loop over sizes - for idx, shell_pos in enumerate(shell_positions): - if shell_pos.shape[0] == shell_species.shape[0]: - - # Save shell as xyz file - mol = Molecule( - shell_species, shell_pos, charge=round(sum(charges)) - ) - mol.to( - os.path.join( - save_dir, - system_name, - solute_atoms_name, - f"coord={c}", - f"size{shell_size}_selection{idx}.xyz", - ), - "xyz", + # Read a structure and metadata file + # TODO: add charges + logging.info("Reading structure and metadata files") + + # Read metadata + with open(os.path.join(input_dir, "metadata_system.json")) as f: + metadata = json.load(f) + + residue_to_species_and_type_mapping = { + k: (v1, v2) + for k, v1, v2 in zip( + metadata["residue"], metadata["species"], metadata["solute_or_solvent"] + ) + } + + solute_resnames = [ + k for k, v in residue_to_species_and_type_mapping.items() if v[1] == "solute" + ] + solvent_resnames = [ + k for k, v in residue_to_species_and_type_mapping.items() if v[1] == "solvent" + ] + + # Read a structure + structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) + + # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash + # Choose the N most diverse in each bin + # Repeat this for each solvent + logging.info("Extracting solvation shells from MD trajectory") + expanded_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + if i > 10: + break + + for residue, (species, _type) in residue_to_species_and_type_mapping.items(): + # TODO: instead loop over all solute residues + if _type == "solute" and species == "Li+": + # extract all atoms in this solute + solute_molecules = [ + res for res in st.residue if res.pdbres == f"{residue} " + ] + central_solute_nums = [mol.molecule_number for mol in solute_molecules] + # Extract solvation shells containing entire residues within 3 angstroms of each molecule + # if only part of a residue is within the radius, include the whole thing + shells = [ + set( + analyze.evaluate_asl( + st, f"fillres within {radii[0]} mol {mol_num}" ) + ) + for mol_num in central_solute_nums + ] + + # Now expand the shells + for shell, central_solute in zip(shells, central_solute_nums): + expanded_shell = expand_shell( + st, + shell, + central_solute, + radii[0], + solute_resnames, + max_shell_size=200, + ) + expanded_shells.append(expanded_shell) + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells by similarity") + grouped_shells = group_with_comparison(expanded_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [renumber_molecules_to_match(items) for items in grouped_shells] + + # Now extract the top N most diverse shells from each group + logging.info("Extracting top N most diverse shells from each group") + final_shells = [] + # example grouping - set of structures + for shell_group in grouped_shells: + # group is a list of structures + import pdb + + pdb.set_trace() + top_n_structures = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(top_n_structures) + + # Save the final shells + logging.info("Saving final solvation shells") + save_path = os.path.join(save_dir, system_name) + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + st.write(os.path.join(save_path, f"shell_{i}.xyz")) if __name__ == "__main__": @@ -216,29 +146,19 @@ def extract_solvation_shells( parser.add_argument( "--system_name", type=str, help="Name of system used for directory naming" ) - parser.add_argument( - "--solute_atoms", - type=parse_list_of_lists, - help="Which solute atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", - ) parser.add_argument( - "--solvent_atoms", - type=parse_list_of_lists, - help="Which solvent atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", + "--radii", + type=list, + default=[3, 6], + help="List of solvation shell radii to extract", ) - parser.add_argument( - "--min_coord", type=int, help="Minimum shell coordination number to extract" - ) - parser.add_argument( - "--max_coord", type=int, help="Maximum shell coordination number to extract" - ) parser.add_argument( "--top_n", type=int, default=20, - help="Number of most diverse shells to extract per coordination number", + help="Number of most diverse shells to extract per topology", ) args = parser.parse_args() @@ -247,9 +167,6 @@ def extract_solvation_shells( args.input_dir, args.save_dir, args.system_name, - args.solute_atoms, - args.solvent_atoms, - args.min_coord, - args.max_coord, + args.radii, args.top_n, ) diff --git a/electrolytes/solvation_shell_extract_old.py b/electrolytes/solvation_shell_extract_old.py new file mode 100644 index 0000000..7c8e986 --- /dev/null +++ b/electrolytes/solvation_shell_extract_old.py @@ -0,0 +1,255 @@ +import os +import logging +import argparse +import random +import numpy as np +from tqdm import tqdm +from typing import List +from collections import defaultdict +import matplotlib.pyplot as plt +import MDAnalysis as mda +from solvation_analysis.solute import Solute +from solvation_analysis._column_names import FRAME, SOLUTE_IX +from pymatgen.core.structure import Molecule +from solvation_shell_utils import ( + filter_by_rmsd, + wrap_positions, + extract_charges_from_lammps_file, +) +from utils import parse_list_of_lists + + +def extract_solvation_shells( + input_dir: str, + save_dir: str, + system_name: str, + solute_atoms: List[str], + solvent_atoms: List[List[str]], + min_coord: int, + max_coord: int, + top_n: int, +): + """ + Given a MD trajectory in a PDB file, perform a solvation analysis + on the specified solute to extract the first solvation shell. For each coordination number in the specified range, + extract and save the top_n most diverse snapshots based on a RMSD criterion. + + Args: + input_dir: Path to 1) the PDB file containing the MD trajectory and 2) the LAMMPS file containing the initial structure (used to extract partial charges). + save_dir: Directory in which to save extracted solvation shells. + system_name: Name of the system - used for naming the save directory. + solute_atoms: List of names (in the PDB file) of the solute atom types (e.g NA0) with which to perform the solvation analysis. + solvent_atoms: List of names (in the PDB file) of the solvent atom types with which to perform the solvation analysis. + min_coord: Minimum coordination number to consider. + max_coord: Maximum coordination number to consider. + top_n: Number of snapshots to extract per coordination number. + """ + solute_atoms_name = " ".join(solute_atoms) + # Create save directory + os.makedirs(os.path.join(save_dir, system_name, solute_atoms_name), exist_ok=True) + + # Read charges from LAMMPS file + lammps_file_path = os.path.join(input_dir, "system.data") + charges = extract_charges_from_lammps_file(lammps_file_path) + + # Initialize MDA Universe + pdb_file_path = os.path.join(input_dir, "system_output.pdb") + universe = mda.Universe(pdb_file_path) + + # Add PBC box + with open(pdb_file_path) as file: + dimension_lines = file.readlines()[1] + a = float(dimension_lines.split()[1]) + b = float(dimension_lines.split()[2]) + c = float(dimension_lines.split()[3]) + universe.dimensions = [a, b, c, 90, 90, 90] + + lattices = np.array([a, b, c])[None][None] + + # Choose solute atom + # TODO: try to join multiple atoms in the same solute, doesn't currently work + solute_query = " or ".join(f"name {atom}" for atom in solute_atoms) + solute = universe.select_atoms(solute_query) + # other_query = " or ".join(f"name {atom}" for atom in other_solute_atoms) + # other_solu = universe.select_atoms(other_query) + + logging.info("Translating atoms to solute center of mass") + for ts in tqdm(universe.trajectory): + ts.dimensions = universe.dimensions + solu_center = solute.center_of_mass(wrap=True) + dim = ts.triclinic_dimensions + box_center = np.sum(dim, axis=0) / 2 + universe.atoms.translate(box_center - solu_center) + + universe.atoms.unwrap() + + # TODO: need to remove the other components of the solute from the solvent atoms? Doesn't matter since the other solute atom won't be close? + + # This doesn't handle multiple solvents + solvent = ( + universe.atoms - solute + ) # TODO: might need to count anything other than the solute of interest as a potential solvent + # TODO: set an upper cutoff for solute-solvent interactions + + solute_name = "".join(atom for atom in solute_atoms) + + logging.info("Running solvation analysis") + # Identify the cutoff for the first solvation shell, based on the MD trajectory + + # discovered that the reason the analysis was failing was because the default cutoff region of 6.5 was too small for the Cl04 anion + kernel_kwargs = {"cutoff_region": (1.5, 8)} + solv_anal = Solute.from_atoms( + solute, + {"solvent": solvent}, + solute_name=solute_name, + kernel_kwargs=kernel_kwargs, + ) + # TODO: subsample fewer solutes to speed up the analysis + + solv_anal.run() # which solute's radii is this using? + + max_radii = 0 + max_name = "" + for solute_name in solv_anal.atom_solutes.keys(): + radii = solv_anal.atom_solutes[solute_name].radii["solvent"] + if radii > max_radii: + max_radii = radii + max_name = solute_name + + # TODO: what do we do with this max or mean radii? Can we need to use it to re-run the analysis? + + # except AssertionError: + # logging.info("Failed to automatically find the radius, trying again with a heuristic radius") + # heuristic_radii = 2.5 # TODO: add heuristic radii based on effective sizes of solute and solvent + # solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name = solute_name, radii={'solvent': heuristic_radii}) + # solv_anal.run() + + # Plot the RDF + solv_anal.plot_solvation_radius(max_name, "solvent") + plt.savefig( + os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png") + ) + + # There's probably a much faster way to do this + # But for now, we're prototyping, so slow is okay + + # Store the solvation shells with different numbers of solvents (sorted from highest to lowest frequency) + shells = dict() + for j in solv_anal.speciation.speciation_fraction["solvent"]: + shells[j] = solv_anal.speciation.get_shells({"solvent": j}) + + # Now let's try getting the most diverse structures for each particular coordination number + # This is also a bit slow, particularly for the more common and/or larger solvent shells + + # TODO: instead of specifying a range of coordination numbers, we could specify the top n most common coordination numbers (but we also probably want to extract rare configurations) + for c in range(min_coord, max_coord + 1): + if c in shells.keys(): + logging.info( + f"Processing {len(shells[c])} shells with coordination number {c}" + ) + os.makedirs( + os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), + exist_ok=True, + ) + shell_species = [] + shell_positions = [] + # Extract the shell positions + + for i, (index, _) in tqdm(enumerate(shells[c].iterrows())): + universe.atoms.unwrap() + frame, solute_idx = index + shell = solv_anal.solvation_data.xs( + (frame, solute_idx), level=(FRAME, SOLUTE_IX) + ) + shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) + # TODO: assertion that compositions/element orderings are the same + if len(shell.atoms.elements) > len(shell_species): + shell_species = shell.atoms.elements + shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) + if i > 1000: # TODO: don't hardcode this + break + + by_num_atoms = defaultdict(list) + for sps in shell_positions: + by_num_atoms[len(sps)].append(sps) + + # filter by number of atoms per shell + selections_by_num_atoms = { + num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) + for num_atoms, shells_with_num_atoms in by_num_atoms.items() + } + + for ( + shell_size, + shell_positions, + ) in selections_by_num_atoms.items(): # loop over sizes + for idx, shell_pos in enumerate(shell_positions): + if shell_pos.shape[0] == shell_species.shape[0]: + + # Save shell as xyz file + mol = Molecule( + shell_species, shell_pos, charge=round(sum(charges)) + ) + mol.to( + os.path.join( + save_dir, + system_name, + solute_atoms_name, + f"coord={c}", + f"size{shell_size}_selection{idx}.xyz", + ), + "xyz", + ) + + +if __name__ == "__main__": + logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) + random.seed(10) + + parser = argparse.ArgumentParser() + parser.add_argument( + "--input_dir", + type=str, + help="Path containing PDB trajectory and LAMMPS data files", + ) + parser.add_argument("--save_dir", type=str, help="Path to save xyz files") + parser.add_argument( + "--system_name", type=str, help="Name of system used for directory naming" + ) + parser.add_argument( + "--solute_atoms", + type=parse_list_of_lists, + help="Which solute atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", + ) + + parser.add_argument( + "--solvent_atoms", + type=parse_list_of_lists, + help="Which solvent atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", + ) + + parser.add_argument( + "--min_coord", type=int, help="Minimum shell coordination number to extract" + ) + parser.add_argument( + "--max_coord", type=int, help="Maximum shell coordination number to extract" + ) + parser.add_argument( + "--top_n", + type=int, + default=20, + help="Number of most diverse shells to extract per coordination number", + ) + + args = parser.parse_args() + + extract_solvation_shells( + args.input_dir, + args.save_dir, + args.system_name, + args.solute_atoms, + args.solvent_atoms, + args.min_coord, + args.max_coord, + args.top_n, + ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index c6b9e96..ba122e0 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,11 +1,84 @@ import re import numpy as np import random -from typing import List -from rmsd import kabsch_rmsd +from typing import List, Callable +from schrodinger.structutils import analyze +from schrodinger.application.matsci import clusterstruct +from schrodinger.comparison import are_conformers +from schrodinger.application.jaguar.utils import group_with_comparison +from schrodinger.comparison.atom_mapper import ConnectivityAtomMapper +from schrodinger.structutils import rmsd +from schrodinger.structure import Structure -def filter_by_rmsd(coords: List[np.array], n: int = 20) -> List[np.array]: + +def rmsd_wrapper(st1: Structure, st2: Structure) -> float: + """ + Wrapper around Schrodinger's RMSD calculation function. + """ + assert ( + st1.atom_total == st2.atom_total + ), "Structures must have the same number of atoms for RMSD calculation" + at_list = list(range(1, st1.atom_total + 1)) + return rmsd.calculate_in_place_rmsd(st1, at_list, st2, at_list, use_symmetry=True) + + +def expand_shell( + st: Structure, + shell_ats: List[int], + central_solute: int, + radius: float, + solute_res_names: List[str], + max_shell_size: int = 200, +) -> Structure: + """ + Expands a solvation shell. If there are any (non-central) solutes present in the shell, + recursively include shells around those solutes. + First, gets the molecule numbers of solute molecules that are within the radius + and not already expanded around. Then, continuously expand around them as long as we don't hit an atom limit. + Args: + st: Entire structure from the PDB file + shell_ats: Set of atoms in a shell (1-indexed) + central_solute: Index of the central solute atom in the shell + radius: Solvation radius (Angstroms) to consider + solute_res_names: List of residue names that correspond to solute atoms in the simulation + max_shell_size: Maximum size (in atoms) of the expanded shell + Returns: + Structure object containing the expanded solvation shell + """ + solutes_included = set([central_solute]) + while len(shell_ats) < max_shell_size: + new_solutes = set() + for at in shell_ats: + # atom is part of a non-central solute molecule - should expand the shell + if ( + st.atom[at].molecule_number not in solutes_included + and st.atom[at].getResidue().pdbres in solute_res_names + ): + new_solutes.add(st.atom[at].molecule_number) + + if new_solutes: + # add entire residues within solvation shell radius of any extra solute atoms + shell_ats.update( + analyze.evaluate_asl( + st, + f'fillres within {radius} mol {",".join([str(i) for i in new_solutes])}', + ) + ) + solutes_included.update(new_solutes) + else: + break + + final_structure = st.extract(sorted(shell_ats), copy_props=True) + # contract everthing to be centered on our molecule of interest + # (this will also handle if a molecule is split across a PBC) + # clusterstruct.contract_structure2( + # final_structure, contract_on_atoms=[central_solute] + # ) + return final_structure + + +def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: """ From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. @@ -13,76 +86,34 @@ def filter_by_rmsd(coords: List[np.array], n: int = 20) -> List[np.array]: by assuming that the random seed point is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we ran this function multiple times, we would get different results. Args: - coords: list of np.arrays of atom coordinates. Must all have the same shape ([N_atoms, 3]), and must all reflect the same atom order! - Note that this latter requirement shouldn't be a problem, specifically when dealing with IonSolvR data. - n: number of most diverse coordinates to return + shell: List of Schrodinger structure objects containing solvation shells + n: number of most diverse shells to return Returns: - list of np.arrays of diverse atom coordinates + List of n Schrodinger structures that are the most diverse in terms of minimum RMSD """ - seed_point = random.randint(0, len(coords) - 1) + seed_point = random.randint(0, len(shells) - 1) states = {seed_point} - min_rmsds = np.array( - [kabsch_rmsd(coords[seed_point], coord, translate=True) for coord in coords] - ) + min_rmsds = np.array([rmsd_wrapper(shells[seed_point], shell) for shell in shells]) for _ in range(n - 1): best = np.argmax(min_rmsds) min_rmsds = np.minimum( min_rmsds, - np.array( - [kabsch_rmsd(coords[best], coord, translate=True) for coord in coords] - ), + np.array([rmsd_wrapper(shells[best], shell) for shell in shells]), ) states.add(best) - return [coords[i] for i in states] + return [shells[i] for i in states] -def wrap_positions(positions: np.array, lattices: np.array) -> np.array: - """ - Wraps input positions based on periodic boundary conditions. - Args: - positions: numpy array of positions, shape [N_atoms, 3] - lattices: numpy array representing dimensions of simulation box, shape [1, 1, 3] - Returns: - numpy array of wrapped_positions, shape [N_atoms, 3] +def renumber_molecules_to_match(mol_list): """ - displacements = positions[:, np.newaxis, :] - positions[np.newaxis, :, :] - idx = np.where(displacements > lattices / 2)[0] - dim = np.where(displacements > lattices / 2)[2] - if idx.shape[0] > 0: - positions[idx, dim] -= lattices[0, 0, dim] - return positions - - -def extract_charges_from_lammps_file(file_path: str) -> List[float]: + Ensure that topologically equivalent sites are equivalently numbered """ - Extracts partial charges of each atom from a LAMMPS file. - Args: - file_path (str): path to the LAMMPS file - Returns: - charges: list of partial charges of length N_atoms - """ - with open(file_path, "r") as file: - lines = file.readlines() - - atoms_section = False - charges = [] - first = False - for line in lines: - if "Atoms" in line: - atoms_section = True - first = True - continue - if atoms_section: - if line.strip() == "": - if not first: - atoms_section = False - continue - first = False - parts = re.split(r"\s+", line.strip()) - # Assuming the format is: atom-ID molecule-ID atom-type charge x y z - charge = float(parts[3]) - charges.append(charge) - - return charges + mapper = ConnectivityAtomMapper(use_chirality=False) + atlist = range(1, mol_list[0].atom_total + 1) + renumbered_mols = [mol_list[0]] + for mol in mol_list[1:]: + _, r_mol = mapper.reorder_structures(mol_list[0], atlist, mol, atlist) + renumbered_mols.append(r_mol) + return renumbered_mols diff --git a/electrolytes/testfiles/Al_ClO4/system.data b/electrolytes/testfiles/Al_ClO4/system.data deleted file mode 100644 index 12256fd..0000000 --- a/electrolytes/testfiles/Al_ClO4/system.data +++ /dev/null @@ -1,41322 +0,0 @@ -LAMMPS Description - - 8352 atoms - 7514 bonds - 12396 angles - 10250 dihedrals - 2750 impropers - - 24 atom types - 21 bond types - 35 angle types - 41 dihedral types - 11 improper types - - -25.0 25.0 xlo xhi - -25.0 25.0 ylo yhi - -25.0 25.0 zlo zhi - -Masses - -1 26.98 # Al -2 35.45 # Cl_clo4 -3 15.99 # O_clo4 -4 12.011 # type1_c_unk_edadc -5 12.011 # type2_c_unk_edadc -6 14.007 # type3_n_unk_edadc -7 12.011 # type4_c_unk_edadc -8 12.011 # type5_c_unk_edadc -9 14.007 # type6_n_unk_edadc -10 12.011 # type7_c_unk_edadc -11 12.011 # type8_c_unk_edadc -12 1.008 # type9_h_unk_edadc -13 1.008 # type10_h_unk_edadc -14 1.008 # type11_h_unk_edadc -15 1.008 # type12_h_unk_edadc -16 1.008 # type13_h_unk_edadc -17 1.008 # type14_h_unk_edadc -18 1.008 # type15_h_unk_edadc -19 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13.454 -1815 481 3 -0.4569 16.905 -14.908 12.787 -1816 481 3 -0.4569 14.676 -14.231 12.872 -1817 481 3 -0.4569 15.806 -14.775 14.839 -1818 482 2 0.8276 20.357 3.346 19.094 -1819 482 3 -0.4569 21.218 4.373 18.601 -1820 482 3 -0.4569 22.549 3.869 18.493 -1821 482 3 -0.4569 20.763 4.798 17.316 -1822 482 3 -0.4569 21.2 5.481 19.503 -1823 483 2 0.8276 -24.68 13.07 13.931 -1824 483 3 -0.4569 -23.891 12.205 13.114 -1825 483 3 -0.4569 -24.268 12.366 11.746 -1826 483 3 -0.4569 -22.51 12.534 13.268 -1827 483 3 -0.4569 -24.105 10.85 13.51 -1828 484 2 0.8276 14.804 1.478 20.749 -1829 484 3 -0.4569 14.909 2.479 19.736 -1830 484 3 -0.4569 15.539 1.923 18.581 -1831 484 3 -0.4569 13.605 2.944 19.389 -1832 484 3 -0.4569 15.69 3.57 20.224 -1833 485 2 0.8276 5.209 17.502 1.666 -1834 485 3 -0.4569 6.304 17.201 0.801 -1835 485 3 -0.4569 7.463 16.91 1.583 -1836 485 3 -0.4569 5.977 16.067 -0.004 -1837 485 3 -0.4569 6.568 18.323 -0.041 -1838 486 2 0.8276 7.886 15.936 -3.562 -1839 486 3 -0.4569 7.829 15.568 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-18.955 -1864 491 3 -0.4569 21.356 -14.344 -20.207 -1865 491 3 -0.4569 22.009 -15.604 -20.054 -1866 491 3 -0.4569 20.015 -14.554 -20.649 -1867 491 3 -0.4569 22.058 -13.559 -21.171 -1868 492 2 0.8276 11.538 0.874 -10.319 -1869 492 3 -0.4569 11.625 0.852 -8.894 -1870 492 3 -0.4569 10.507 0.143 -8.36 -1871 492 3 -0.4569 12.833 0.201 -8.501 -1872 492 3 -0.4569 11.621 2.191 -8.397 -1873 493 2 0.8276 23.314 -20.503 8.11 -1874 493 3 -0.4569 23.394 -19.542 9.163 -1875 493 3 -0.4569 24.684 -19.608 9.772 -1876 493 3 -0.4569 23.186 -18.234 8.63 -1877 493 3 -0.4569 22.392 -19.823 10.141 -1878 494 2 0.8276 5.003 -0.072 -23.447 -1879 494 3 -0.4569 4.607 0.859 -22.44 -1880 494 3 -0.4569 4.574 2.175 -22.994 -1881 494 3 -0.4569 3.308 0.514 -21.958 -1882 494 3 -0.4569 5.542 0.82 -21.362 -1883 495 2 0.8276 -10.595 0.189 19.09 -1884 495 3 -0.4569 -10.129 0.952 17.977 -1885 495 3 -0.4569 -10.084 2.334 18.332 -1886 495 3 -0.4569 -8.821 0.512 17.611 -1887 495 3 -0.4569 -11.018 0.774 16.873 -1888 496 2 0.8276 -22.292 6.902 13.349 -1889 496 3 -0.4569 -22.758 5.597 13.692 -1890 496 3 -0.4569 -22.102 4.627 12.874 -1891 496 3 -0.4569 -22.469 5.334 15.065 -1892 496 3 -0.4569 -24.167 5.524 13.478 -1893 497 2 0.8276 16.366 -23.335 15.775 -1894 497 3 -0.4569 17.636 -23.235 15.13 -1895 497 3 -0.4569 17.514 -23.649 13.769 -1896 497 3 -0.4569 18.088 -21.882 15.177 -1897 497 3 -0.4569 18.577 -24.075 15.8 -1898 498 2 0.8276 7.898 5.897 -23.817 -1899 498 3 -0.4569 8.082 4.618 -23.211 -1900 498 3 -0.4569 7.981 3.599 -24.206 -1901 498 3 -0.4569 9.373 4.562 -22.603 -1902 498 3 -0.4569 7.078 4.414 -22.217 -1903 499 2 0.8276 22.097 -9.472 16.952 -1904 499 3 -0.4569 22.977 -10.587 17.095 -1905 499 3 -0.4569 22.81 -11.471 15.987 -1906 499 3 -0.4569 24.327 -10.125 17.135 -1907 499 3 -0.4569 22.674 -11.279 18.306 -1908 500 2 0.8276 -24.935 22.246 5.174 -1909 500 3 -0.4569 -23.905 22.25 6.163 -1910 500 3 -0.4569 -22.696 22.751 5.59 -1911 500 3 -0.4569 -24.295 23.084 7.254 -1912 500 3 -0.4569 -23.692 20.919 6.633 -1913 501 2 0.8276 14.285 -22.89 -1.637 -1914 501 3 -0.4569 14.555 -21.59 -1.11 -1915 501 3 -0.4569 14.364 -21.601 0.305 -1916 501 3 -0.4569 15.904 -21.229 -1.405 -1917 501 3 -0.4569 13.667 -20.643 -1.703 -1918 502 2 0.8276 3.374 25.0 -13.823 -1919 502 3 -0.4569 4.148 24.176 -12.952 -1920 502 3 -0.4569 5.042 23.373 -13.724 -1921 502 3 -0.4569 4.899 25.0 -12.06 -1922 502 3 -0.4569 3.278 23.329 -12.2 -1923 503 2 0.8276 24.332 19.362 -14.146 -1924 503 3 -0.4569 23.894 20.655 -14.565 -1925 503 3 -0.4569 23.381 21.371 -13.442 -1926 503 3 -0.4569 24.995 21.372 -15.124 -1927 503 3 -0.4569 22.869 20.513 -15.549 -1928 504 2 0.8276 -16.854 -24.144 -21.79 -1929 504 3 -0.4569 -15.684 -23.33 -21.705 -1930 504 3 -0.4569 -14.993 -23.614 -20.488 -1931 504 3 -0.4569 -14.828 -23.61 -22.813 -1932 504 3 -0.4569 -16.059 -21.953 -21.728 -1933 505 2 0.8276 0.56 20.746 -13.863 -1934 505 3 -0.4569 1.318 21.323 -14.926 -1935 505 3 -0.4569 2.662 20.845 -14.868 -1936 505 3 -0.4569 0.737 20.957 -16.178 -1937 505 3 -0.4569 1.313 22.745 -14.797 -1938 506 2 0.8276 -4.314 -0.23 -16.447 -1939 506 3 -0.4569 -3.199 -1.112 -16.579 -1940 506 3 -0.4569 -2.753 -1.117 -17.935 -1941 506 3 -0.4569 -2.139 -0.67 -15.731 -1942 506 3 -0.4569 -3.591 -2.433 -16.203 -1943 507 2 0.8276 4.178 -17.452 11.014 -1944 507 3 -0.4569 4.522 -18.747 11.508 -1945 507 3 -0.4569 5.792 -18.688 12.157 -1946 507 3 -0.4569 3.53 -19.18 12.44 -1947 507 3 -0.4569 4.587 -19.669 10.419 -1948 508 2 0.8276 -15.92 1.723 13.62 -1949 508 3 -0.4569 -16.264 0.454 14.178 -1950 508 3 -0.4569 -16.122 -0.559 13.181 -1951 508 3 -0.4569 -15.397 0.166 15.275 -1952 508 3 -0.4569 -17.616 0.486 14.634 -1953 509 2 0.8276 1.657 -14.966 20.349 -1954 509 3 -0.4569 0.738 -15.667 19.512 -1955 509 3 -0.4569 1.238 -16.978 19.247 -1956 509 3 -0.4569 -0.526 -15.764 20.17 -1957 509 3 -0.4569 0.581 -14.96 18.281 -1958 510 2 0.8276 8.682 17.649 -20.766 -1959 510 3 -0.4569 8.7 16.247 -20.5 -1960 510 3 -0.4569 7.896 15.568 -21.465 -1961 510 3 -0.4569 10.042 15.765 -20.576 -1962 510 3 -0.4569 8.18 16.004 -19.193 -1963 511 2 0.8276 -5.672 -5.767 -13.591 -1964 511 3 -0.4569 -5.698 -4.669 -14.503 -1965 511 3 -0.4569 -4.824 -3.641 -14.037 -1966 511 3 -0.4569 -5.269 -5.111 -15.791 -1967 511 3 -0.4569 -7.028 -4.158 -14.594 -1968 512 2 0.8276 13.6 -3.607 -5.383 -1969 512 3 -0.4569 14.014 -2.328 -5.865 -1970 512 3 -0.4569 13.837 -2.272 -7.281 -1971 512 3 -0.4569 13.227 -1.31 -5.247 -1972 512 3 -0.4569 15.391 -2.124 -5.549 -1973 513 2 0.8276 -13.155 3.824 16.587 -1974 513 3 -0.4569 -13.064 3.659 18.003 -1975 513 3 -0.4569 -11.904 4.336 18.488 -1976 513 3 -0.4569 -14.228 4.208 18.621 -1977 513 3 -0.4569 -12.969 2.269 18.314 -1978 514 2 0.8276 2.568 2.871 22.27 -1979 514 3 -0.4569 1.276 2.31 22.037 -1980 514 3 -0.4569 0.514 3.193 21.215 -1981 514 3 -0.4569 1.416 1.05 21.38 -1982 514 3 -0.4569 0.606 2.124 23.284 -1983 515 2 0.8276 13.96 0.057 11.53 -1984 515 3 -0.4569 13.341 -0.873 12.42 -1985 515 3 -0.4569 12.861 -1.995 11.679 -1986 515 3 -0.4569 14.296 -1.314 13.385 -1987 515 3 -0.4569 12.248 -0.239 13.085 -1988 516 2 0.8276 25.015 -15.668 11.766 -1989 516 3 -0.4569 23.729 -15.644 12.386 -1990 516 3 -0.4569 23.064 -14.425 12.055 -1991 516 3 -0.4569 22.956 -16.749 11.92 -1992 516 3 -0.4569 23.883 -15.732 13.803 -1993 517 2 0.8276 -8.614 14.48 -16.107 -1994 517 3 -0.4569 -7.551 13.587 -15.774 -1995 517 3 -0.4569 -6.312 14.298 -15.778 -1996 517 3 -0.4569 -7.78 13.038 -14.476 -1997 517 3 -0.4569 -7.496 12.533 -16.735 -1998 518 2 0.8276 6.66 -21.983 20.897 -1999 518 3 -0.4569 6.735 -22.964 19.862 -2000 518 3 -0.4569 5.746 -23.97 20.086 -2001 518 3 -0.4569 6.502 -22.341 18.599 -2002 518 3 -0.4569 8.031 -23.562 19.867 -2003 519 2 0.8276 2.344 5.621 -4.008 -2004 519 3 -0.4569 1.446 6.731 -3.973 -2005 519 3 -0.4569 0.527 6.635 -5.061 -2006 519 3 -0.4569 0.726 6.721 -2.74 -2007 519 3 -0.4569 2.188 7.946 -4.082 -2008 520 2 0.8276 15.576 -9.867 -4.042 -2009 520 3 -0.4569 14.6 -9.075 -4.719 -2010 520 3 -0.4569 14.514 -7.792 -4.099 -2011 520 3 -0.4569 14.979 -8.919 -6.086 -2012 520 3 -0.4569 13.33 -9.723 -4.647 -2013 521 2 0.8276 -12.003 21.003 -22.526 -2014 521 3 -0.4569 -11.798 19.591 -22.584 -2015 521 3 -0.4569 -13.009 18.95 -22.987 -2016 521 3 -0.4569 -10.768 19.299 -23.529 -2017 521 3 -0.4569 -11.412 19.113 -21.295 -2018 522 2 0.8276 -13.604 2.551 21.512 -2019 522 3 -0.4569 -13.322 1.369 20.763 -2020 522 3 -0.4569 -13.328 0.238 21.635 -2021 522 3 -0.4569 -14.318 1.197 19.754 -2022 522 3 -0.4569 -12.039 1.489 20.149 -2023 523 2 0.8276 -7.834 18.949 -17.892 -2024 523 3 -0.4569 -8.521 17.847 -17.298 -2025 523 3 -0.4569 -9.702 18.316 -16.646 -2026 523 3 -0.4569 -8.879 16.907 -18.312 -2027 523 3 -0.4569 -7.669 17.215 -16.342 -2028 524 2 0.8276 -5.46 20.672 15.134 -2029 524 3 -0.4569 -6.026 21.856 15.697 -2030 524 3 -0.4569 -6.478 22.714 14.649 -2031 524 3 -0.4569 -7.129 21.505 16.533 -2032 524 3 -0.4569 -5.037 22.534 16.472 -2033 525 2 0.8276 8.672 6.302 -6.693 -2034 525 3 -0.4569 7.272 6.579 -6.638 -2035 525 3 -0.4569 7.071 7.967 -6.375 -2036 525 3 -0.4569 6.672 6.24 -7.888 -2037 525 3 -0.4569 6.675 5.806 -5.597 -2038 526 2 0.8276 -9.299 -19.809 22.673 -2039 526 3 -0.4569 -9.211 -18.58 21.953 -2040 526 3 -0.4569 -8.223 -17.744 22.556 -2041 526 3 -0.4569 -8.845 -18.847 20.599 -2042 526 3 -0.4569 -10.476 -17.919 21.983 -2043 527 2 0.8276 8.773 -20.065 -24.999 -2044 527 3 -0.4569 9.836 -19.534 -24.206 -2045 527 3 -0.4569 9.476 -18.235 -23.735 -2046 527 3 -0.4569 10.074 -20.395 -23.092 -2047 527 3 -0.4569 11.02 -19.441 -24.998 -2048 528 2 0.8276 18.906 -14.169 22.427 -2049 528 3 -0.4569 20.18 -14.739 22.726 -2050 528 3 -0.4569 20.991 -13.77 23.391 -2051 528 3 -0.4569 20.005 -15.875 23.574 -2052 528 3 -0.4569 20.817 -15.142 21.514 -2053 529 2 0.8276 6.721 3.556 -6.093 -2054 529 3 -0.4569 6.409 2.262 -5.577 -2055 529 3 -0.4569 5.565 2.395 -4.433 -2056 529 3 -0.4569 5.735 1.5 -6.579 -2057 529 3 -0.4569 7.615 1.595 -5.203 -2058 530 2 0.8276 4.849 0.174 13.297 -2059 530 3 -0.4569 4.044 -0.472 12.311 -2060 530 3 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zlo zhi - -Masses - -1 6.94 # Li -2 30.974 # P -3 18.998 # F -4 12.011 # type1_c_unk_6dedc -5 12.011 # type2_c_unk_6dedc -6 15.999 # type3_o_unk_6dedc -7 12.011 # type4_c_unk_6dedc -8 15.999 # type5_o_unk_6dedc -9 15.999 # type6_o_unk_6dedc -10 1.008 # type7_h_unk_6dedc -11 1.008 # type8_h_unk_6dedc -12 1.008 # type9_h_unk_6dedc -13 1.008 # type10_h_unk_6dedc -14 12.011 # type1_c_unk_29441 -15 12.011 # type2_c_unk_29441 -16 15.999 # type3_o_unk_29441 -17 12.011 # type4_c_unk_29441 -18 15.999 # type5_o_unk_29441 -19 15.999 # type6_o_unk_29441 -20 12.011 # type7_c_unk_29441 -21 1.008 # type8_h_unk_29441 -22 1.008 # type9_h_unk_29441 -23 1.008 # type10_h_unk_29441 -24 1.008 # type11_h_unk_29441 -25 1.008 # type12_h_unk_29441 -26 1.008 # type13_h_unk_29441 -27 1.008 # type14_h_unk_29441 -28 1.008 # type15_h_unk_29441 - -Atoms # full - -1 1 1 1 -17.112 1.014 -10.684 -2 2 1 1 16.744 23.352 24.34 -3 3 1 1 16.354 -14.783 -22.587 -4 4 1 1 3.629 -17.789 8.111 -5 5 1 1 16.114 -11.644 22.39 -6 6 1 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-1932 411 7 0.55660000 18.592 -20.815 10.694 -1933 411 8 -0.36810000 19.475 -20.089 11.115 -1934 411 9 -0.32080000 17.29 -20.756 11.093 -1935 411 10 0.13560000 16.689 -22.699 11.326 -1936 411 11 0.13560000 15.613 -21.697 10.313 -1937 411 12 0.13550000 17.18 -21.656 8.487 -1938 411 13 0.13550000 17.485 -23.293 9.131 -1939 412 4 -0.04380000 -2.885 -11.649 14.641 -1940 412 5 -0.04400000 -1.763 -10.698 14.384 -1941 412 6 -0.32210000 -1.746 -9.909 15.559 -1942 412 7 0.55660000 -3.014 -9.943 16.067 -1943 412 8 -0.36810000 -3.413 -9.229 16.97 -1944 412 9 -0.32080000 -3.773 -10.881 15.432 -1945 412 10 0.13560000 -2.569 -12.523 15.222 -1946 412 11 0.13560000 -3.371 -11.984 13.721 -1947 412 12 0.13550000 -1.959 -10.044 13.527 -1948 412 13 0.13550000 -0.807 -11.207 14.239 -1949 413 4 -0.04380000 6.107 -19.865 -6.776 -1950 413 5 -0.04400000 6.666 -18.48 -6.777 -1951 413 6 -0.32210000 6.758 -18.178 -5.398 -1952 413 7 0.55660000 5.815 -18.942 -4.77 -1953 413 8 -0.36810000 5.484 -18.809 -3.605 -1954 413 9 -0.32080000 5.293 -19.874 -5.618 -1955 413 10 0.13560000 6.884 -20.63 -6.662 -1956 413 11 0.13560000 5.518 -20.081 -7.671 -1957 413 12 0.13550000 5.99 -17.758 -7.249 -1958 413 13 0.13550000 7.646 -18.424 -7.257 -1959 414 4 -0.04380000 8.185 12.306 17.598 -1960 414 5 -0.04400000 7.153 11.23 17.505 -1961 414 6 -0.32210000 7.229 10.841 16.146 -1962 414 7 0.55660000 7.698 11.925 15.459 -1963 414 8 -0.36810000 7.715 12.015 14.244 -1964 414 9 -0.32080000 8.144 12.891 16.31 -1965 414 10 0.13560000 9.191 11.909 17.769 -1966 414 11 0.13560000 7.952 13.044 18.371 -1967 414 12 0.13550000 6.143 11.601 17.706 -1968 414 13 0.13550000 7.367 10.386 18.167 -1969 415 4 -0.04380000 -15.527 -0.794 -6.927 -1970 415 5 -0.04400000 -15.175 -0.605 -5.488 -1971 415 6 -0.32210000 -16.254 -1.228 -4.817 -1972 415 7 0.55660000 -17.324 -1.168 -5.666 -1973 415 8 -0.36810000 -18.469 -1.441 -5.351 -1974 415 9 -0.32080000 -16.942 -0.763 -6.91 -1975 415 10 0.13560000 -15.204 -1.767 -7.314 -1976 415 11 0.13560000 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0.13550000 -16.235 12.709 -18.531 -1999 418 4 -0.04380000 -1.125 18.679 -9.919 -2000 418 5 -0.04400000 -1.802 19.724 -10.746 -2001 418 6 -0.32210000 -2.142 20.709 -9.789 -2002 418 7 0.55660000 -2.26 20.061 -8.591 -2003 418 8 -0.36810000 -2.721 20.561 -7.58 -2004 418 9 -0.32080000 -1.793 18.783 -8.675 -2005 418 10 0.13560000 -0.062 18.893 -9.763 -2006 418 11 0.13560000 -1.234 17.676 -10.339 -2007 418 12 0.13550000 -2.723 19.355 -11.21 -2008 418 13 0.13550000 -1.147 20.136 -11.518 -2009 419 4 -0.04380000 -14.768 -0.087 -13.867 -2010 419 5 -0.04400000 -15.552 -0.127 -12.596 -2011 419 6 -0.32210000 -14.736 0.605 -11.702 -2012 419 7 0.55660000 -13.455 0.49 -12.163 -2013 419 8 -0.36810000 -12.465 0.837 -11.543 -2014 419 9 -0.32080000 -13.429 -0.064 -13.409 -2015 419 10 0.13560000 -14.954 0.825 -14.446 -2016 419 11 0.13560000 -14.95 -0.96 -14.5 -2017 419 12 0.13550000 -15.667 -1.146 -12.209 -2018 419 13 0.13550000 -16.537 0.336 -12.696 -2019 420 4 -0.04380000 3.249 -13.977 -1.238 -2020 420 5 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-493 1 1480 1479 1481 -494 1 1483 1482 1484 -495 1 1486 1485 1487 -496 1 1489 1488 1490 -497 1 1492 1491 1493 -498 1 1495 1494 1496 -499 1 1498 1497 1499 -500 1 1501 1500 1502 - diff --git a/electrolytes/utils.py b/electrolytes/utils.py deleted file mode 100644 index ffb6c2a..0000000 --- a/electrolytes/utils.py +++ /dev/null @@ -1,13 +0,0 @@ -import argparse - - -def parse_list_of_lists(value): - try: - # Split by ';' to separate different lists - lists = value.split(";") - # Further split each list by ',' to get individual elements - return [lst.split(",") for lst in lists] - except Exception as e: - raise argparse.ArgumentTypeError( - f"Invalid input for list of lists: {value}. Error: {e}" - ) From d65860fd4239b96a60cebbe6057704c6ab1dae82 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 13:22:13 -0700 Subject: [PATCH 051/117] can extract shells, now need to loop over solutes, apply pbcs and add charges --- electrolytes/solvation_shell_extract.py | 14 ++++------ electrolytes/solvation_shell_utils.py | 37 +++++++++++++------------ 2 files changed, 24 insertions(+), 27 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 36a3c6e..8329053 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -106,23 +106,19 @@ def extract_solvation_shells( # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells by similarity") + logging.info("Grouping solvation shells into conformers") grouped_shells = group_with_comparison(expanded_shells, are_conformers) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [renumber_molecules_to_match(items) for items in grouped_shells] # Now extract the top N most diverse shells from each group - logging.info("Extracting top N most diverse shells from each group") + logging.info(f"Extracting top {top_n} most diverse shells from each group") final_shells = [] # example grouping - set of structures - for shell_group in grouped_shells: - # group is a list of structures - import pdb - - pdb.set_trace() - top_n_structures = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(top_n_structures) + for shell_group in tqdm(grouped_shells): + filtered_shells = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered_shells) # Save the final shells logging.info("Saving final solvation shells") diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index ba122e0..145d960 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -12,17 +12,6 @@ from schrodinger.structure import Structure -def rmsd_wrapper(st1: Structure, st2: Structure) -> float: - """ - Wrapper around Schrodinger's RMSD calculation function. - """ - assert ( - st1.atom_total == st2.atom_total - ), "Structures must have the same number of atoms for RMSD calculation" - at_list = list(range(1, st1.atom_total + 1)) - return rmsd.calculate_in_place_rmsd(st1, at_list, st2, at_list, use_symmetry=True) - - def expand_shell( st: Structure, shell_ats: List[int], @@ -80,10 +69,10 @@ def expand_shell( def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: """ - From a set of coordinates, determine the n most diverse, where "most diverse" means "most different, in terms of minimum RMSD. - We use the Kabsch Algorithm (https://en.wikipedia.org/wiki/Kabsch_algorithm) to align coordinates based on rotation/translation before computing the RMSD. - Note: The Max-Min Diversity Problem is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords - by assuming that the random seed point is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we ran this function multiple times, we would get different results. + From a set of shell coordinates, determine the n most diverse shells, where "most diverse" means "most different, in terms of minimum RMSD. + Note: The Max-Min Diversity Problem (MMDP) is in general NP-hard. This algorithm generates a candidate solution to MMDP for these coords + by assuming that the random seed point is actually in the MMDP set (which there's no reason a priori to assume). As a result, if we ran + this function multiple times, we would get different results. Args: shell: List of Schrodinger structure objects containing solvation shells @@ -93,7 +82,7 @@ def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: """ seed_point = random.randint(0, len(shells) - 1) - states = {seed_point} + final_shell_idxs = {seed_point} min_rmsds = np.array([rmsd_wrapper(shells[seed_point], shell) for shell in shells]) for _ in range(n - 1): best = np.argmax(min_rmsds) @@ -101,9 +90,21 @@ def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: min_rmsds, np.array([rmsd_wrapper(shells[best], shell) for shell in shells]), ) - states.add(best) + final_shell_idxs.add(best) + return [shells[i] for i in final_shell_idxs] - return [shells[i] for i in states] + +def rmsd_wrapper(st1: Structure, st2: Structure) -> float: + """ + Wrapper around Schrodinger's RMSD calculation function. + """ + assert ( + st1.atom_total == st2.atom_total + ), "Structures must have the same number of atoms for RMSD calculation" + if st1 == st2: + return 0.0 + at_list = list(range(1, st1.atom_total + 1)) + return rmsd.calculate_in_place_rmsd(st1, at_list, st2, at_list, use_symmetry=True) def renumber_molecules_to_match(mol_list): From ed22d93c88e40e0ae5137eedf7c196dc43dcaa52 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 13:43:38 -0700 Subject: [PATCH 052/117] loop over solutes --- electrolytes/solvation_shell_extract.py | 112 +++++++++++++----------- 1 file changed, 61 insertions(+), 51 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 8329053..62b3ef3 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -54,28 +54,36 @@ def extract_solvation_shells( ) } - solute_resnames = [ - k for k, v in residue_to_species_and_type_mapping.items() if v[1] == "solute" - ] - solvent_resnames = [ - k for k, v in residue_to_species_and_type_mapping.items() if v[1] == "solvent" - ] + solutes = { + v[0]: k + for k, v in residue_to_species_and_type_mapping.items() + if v[1] == "solute" + } + solute_resnames = list(solutes.keys()) + + solvents = { + v[0]: k + for k, v in residue_to_species_and_type_mapping.items() + if v[1] == "solvent" + } + solvent_resnames = list(solvents.keys()) # Read a structure structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin - # Repeat this for each solvent - logging.info("Extracting solvation shells from MD trajectory") - expanded_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps - if i > 10: - break - - for residue, (species, _type) in residue_to_species_and_type_mapping.items(): - # TODO: instead loop over all solute residues - if _type == "solute" and species == "Li+": + + for species, residue in solutes.items(): + logging.info(f"Extracting solvation shells around {species})") + + for radius in radii: + logging.info(f"Radius = {radius} A") + expanded_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + if i > 10: # TODO: fix this + break + # extract all atoms in this solute solute_molecules = [ res for res in st.residue if res.pdbres == f"{residue} " @@ -86,46 +94,48 @@ def extract_solvation_shells( shells = [ set( analyze.evaluate_asl( - st, f"fillres within {radii[0]} mol {mol_num}" + st, f"fillres within {radius} mol {mol_num}" ) ) for mol_num in central_solute_nums ] - # Now expand the shells - for shell, central_solute in zip(shells, central_solute_nums): - expanded_shell = expand_shell( - st, - shell, - central_solute, - radii[0], - solute_resnames, - max_shell_size=200, - ) - expanded_shells.append(expanded_shell) - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - grouped_shells = group_with_comparison(expanded_shells, are_conformers) - - # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - grouped_shells = [renumber_molecules_to_match(items) for items in grouped_shells] - - # Now extract the top N most diverse shells from each group - logging.info(f"Extracting top {top_n} most diverse shells from each group") - final_shells = [] - # example grouping - set of structures - for shell_group in tqdm(grouped_shells): - filtered_shells = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(filtered_shells) - - # Save the final shells - logging.info("Saving final solvation shells") - save_path = os.path.join(save_dir, system_name) - os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): - st.write(os.path.join(save_path, f"shell_{i}.xyz")) + # Now expand the shells + for shell, central_solute in zip(shells, central_solute_nums): + expanded_shell = expand_shell( + st, + shell, + central_solute, + radius, + solute_resnames, + max_shell_size=200, + ) + expanded_shells.append(expanded_shell) + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + grouped_shells = group_with_comparison(expanded_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [ + renumber_molecules_to_match(items) for items in grouped_shells + ] + + # Now extract the top N most diverse shells from each group + logging.info(f"Extracting top {top_n} most diverse shells from each group") + final_shells = [] + # example grouping - set of structures + for shell_group in tqdm(grouped_shells): + filtered_shells = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered_shells) + + # Save the final shells + logging.info(f"Saving final solvation shells") + save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + st.write(os.path.join(save_path, f"shell_{i}.xyz")) if __name__ == "__main__": From 82fff887303769bfdb7f55e7cb24f60d2c45d6a1 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 13:52:06 -0700 Subject: [PATCH 053/117] fix loop nesting --- electrolytes/solvation_shell_extract.py | 53 ++++++++++++------------- 1 file changed, 25 insertions(+), 28 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 62b3ef3..eba46fa 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -47,26 +47,24 @@ def extract_solvation_shells( with open(os.path.join(input_dir, "metadata_system.json")) as f: metadata = json.load(f) - residue_to_species_and_type_mapping = { - k: (v1, v2) - for k, v1, v2 in zip( - metadata["residue"], metadata["species"], metadata["solute_or_solvent"] - ) - } solutes = { - v[0]: k - for k, v in residue_to_species_and_type_mapping.items() - if v[1] == "solute" - } - solute_resnames = list(solutes.keys()) + species: res + for res, species, type in zip( + metadata["residue"], metadata["species"], metadata["solute_or_solvent"] + ) + if type == "solute" + } # {species: residue name} mapping + solute_resnames = list(solutes.values()) solvents = { - v[0]: k - for k, v in residue_to_species_and_type_mapping.items() - if v[1] == "solvent" - } - solvent_resnames = list(solvents.keys()) + species: res + for res, species, type in zip( + metadata["residue"], metadata["species"], metadata["solute_or_solvent"] + ) + if type == "solvent" + } # {species: residue name} mapping + solvent_resnames = list(solvents.values()) # Read a structure structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) @@ -76,7 +74,6 @@ def extract_solvation_shells( for species, residue in solutes.items(): logging.info(f"Extracting solvation shells around {species})") - for radius in radii: logging.info(f"Radius = {radius} A") expanded_shells = [] @@ -100,17 +97,17 @@ def extract_solvation_shells( for mol_num in central_solute_nums ] - # Now expand the shells - for shell, central_solute in zip(shells, central_solute_nums): - expanded_shell = expand_shell( - st, - shell, - central_solute, - radius, - solute_resnames, - max_shell_size=200, - ) - expanded_shells.append(expanded_shell) + # Now expand the shells + for shell, central_solute in zip(shells, central_solute_nums): + expanded_shell = expand_shell( + st, + shell, + central_solute, + radius, + solute_resnames, + max_shell_size=200, + ) + expanded_shells.append(expanded_shell) # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other From 1ef6e1bbe85b8ae146c9d37b25a16dd8a86ac811 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 14:10:36 -0700 Subject: [PATCH 054/117] add partial charge assignment --- electrolytes/solvation_shell_extract.py | 18 ++++++++++++++++-- electrolytes/utils.py | 18 ++++++++++++++++++ 2 files changed, 34 insertions(+), 2 deletions(-) create mode 100644 electrolytes/utils.py diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index eba46fa..3f915c6 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -2,11 +2,13 @@ import logging logging.basicConfig(level=logging.INFO) + import random import os from tqdm import tqdm import json import argparse +import numpy as np from schrodinger.structure import StructureReader from schrodinger.structutils import analyze @@ -15,6 +17,7 @@ renumber_molecules_to_match, filter_by_rmsd, ) +from utils import validate_metadata_file from schrodinger.comparison import are_conformers from schrodinger.application.jaguar.utils import group_with_comparison from schrodinger.structutils import rmsd @@ -47,6 +50,9 @@ def extract_solvation_shells( with open(os.path.join(input_dir, "metadata_system.json")) as f: metadata = json.load(f) + validate_metadata_file(metadata) + + partial_charges = np.array(metadata["partial_charges"]) solutes = { species: res @@ -54,7 +60,7 @@ def extract_solvation_shells( metadata["residue"], metadata["species"], metadata["solute_or_solvent"] ) if type == "solute" - } # {species: residue name} mapping + } # {species: residue name} mapping solute_resnames = list(solutes.values()) solvents = { @@ -63,7 +69,7 @@ def extract_solvation_shells( metadata["residue"], metadata["species"], metadata["solute_or_solvent"] ) if type == "solvent" - } # {species: residue name} mapping + } # {species: residue name} mapping solvent_resnames = list(solvents.values()) # Read a structure @@ -78,6 +84,10 @@ def extract_solvation_shells( logging.info(f"Radius = {radius} A") expanded_shells = [] for i, st in tqdm(enumerate(structures)): # loop over timesteps + # assign partial charges to atoms + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + if i > 10: # TODO: fix this break @@ -134,6 +144,10 @@ def extract_solvation_shells( for i, st in enumerate(final_shells): st.write(os.path.join(save_path, f"shell_{i}.xyz")) + # Now repeat for solvents + for species, residue in solvents.items(): + pass + if __name__ == "__main__": logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) diff --git a/electrolytes/utils.py b/electrolytes/utils.py new file mode 100644 index 0000000..4c9a690 --- /dev/null +++ b/electrolytes/utils.py @@ -0,0 +1,18 @@ +from typing import Dict + + +def validate_metadata_file(metadata: Dict): + """ + Validates the metadata file to ensure that it contains the necessary fields. + Args: + metadata: Dictionary containing metadata for the system. + """ + required_fields = [ + "residue", + "species", + "solute_or_solvent", + "partial_charges", + ] + for field in required_fields: + if field not in metadata: + raise ValueError(f"Metadata file is missing required field: {field}") From 4a55633a0330bac37dbb065aea3a4ef2026485d9 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 16:53:55 -0700 Subject: [PATCH 055/117] fix pbc wrapping index error --- electrolytes/solvation_shell_extract.py | 6 ++++-- electrolytes/solvation_shell_utils.py | 20 ++++++++++++++++---- 2 files changed, 20 insertions(+), 6 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 3f915c6..7bdaf94 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -122,6 +122,7 @@ def extract_solvation_shells( # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") + # TODO: speed this up grouped_shells = group_with_comparison(expanded_shells, are_conformers) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) @@ -144,8 +145,9 @@ def extract_solvation_shells( for i, st in enumerate(final_shells): st.write(os.path.join(save_path, f"shell_{i}.xyz")) - # Now repeat for solvents + # Now repeat for solvents: for species, residue in solvents.items(): + # TODO: implement pass @@ -167,7 +169,7 @@ def extract_solvation_shells( parser.add_argument( "--radii", type=list, - default=[3, 6], + default=[3], help="List of solvation shell radii to extract", ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 145d960..b73126f 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -35,6 +35,13 @@ def expand_shell( Returns: Structure object containing the expanded solvation shell """ + try: + assert central_solute in shell_ats, "Central solute not in shell" + except AssertionError as e: + print(e) + print(f"Central solute: {central_solute}") + print(f"Shell atoms: {shell_ats}") + import pdb; pdb.set_trace() solutes_included = set([central_solute]) while len(shell_ats) < max_shell_size: new_solutes = set() @@ -57,13 +64,18 @@ def expand_shell( solutes_included.update(new_solutes) else: break + shell_ats = sorted(shell_ats) + final_structure = st.extract(shell_ats, copy_props=True) + + # find index of central solute in the sorted shell_ats (adjust for 1-indexing) + central_solute_idx = shell_ats.index(central_solute) + 1 - final_structure = st.extract(sorted(shell_ats), copy_props=True) # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) - # clusterstruct.contract_structure2( - # final_structure, contract_on_atoms=[central_solute] - # ) + + clusterstruct.contract_structure2( + final_structure, contract_on_atoms=[central_solute_idx] + ) return final_structure From 66b4afd9cfb1207af7b9a1d29fd55e1f8f6b1f90 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 17:23:41 -0700 Subject: [PATCH 056/117] append central atom to shell if not already present, have fully running pipeline, need to test --- electrolytes/solvation_shell_extract.py | 3 ++- electrolytes/solvation_shell_utils.py | 15 ++++++--------- 2 files changed, 8 insertions(+), 10 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 7bdaf94..fa1bc49 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -35,7 +35,7 @@ def extract_solvation_shells( on the specified solute to extract the first solvation shell. Args: - input_dir: Path to 1) the PDB file containing the MD trajectory and 2) the LAMMPS file containing the initial structure (used to extract partial charges). + input_dir: Path to 1) the PDB file containing the MD trajectory (system_output.pdb) and 2) a metadata file (system_metadata.json) save_dir: Directory in which to save extracted solvation shells. system_name: Name of the system - used for naming the save directory. radii: List of solvation shell radii to extract. @@ -143,6 +143,7 @@ def extract_solvation_shells( save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") os.makedirs(save_path, exist_ok=True) for i, st in enumerate(final_shells): + # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) # Now repeat for solvents: diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index b73126f..68f5e55 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,7 +1,7 @@ import re import numpy as np import random -from typing import List, Callable +from typing import List, Set, Callable from schrodinger.structutils import analyze from schrodinger.application.matsci import clusterstruct @@ -14,7 +14,7 @@ def expand_shell( st: Structure, - shell_ats: List[int], + shell_ats: Set[int], central_solute: int, radius: float, solute_res_names: List[str], @@ -35,13 +35,10 @@ def expand_shell( Returns: Structure object containing the expanded solvation shell """ - try: - assert central_solute in shell_ats, "Central solute not in shell" - except AssertionError as e: - print(e) - print(f"Central solute: {central_solute}") - print(f"Shell atoms: {shell_ats}") - import pdb; pdb.set_trace() + # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell + if central_solute not in shell_ats: + shell_ats.add(central_solute) + solutes_included = set([central_solute]) while len(shell_ats) < max_shell_size: new_solutes = set() From ac25b01b71e1c6d946c9016be446b6344ba7fec2 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 17:30:59 -0700 Subject: [PATCH 057/117] cleanup files --- electrolytes/example_for_sanjeev.py | 120 --------- electrolytes/solvation_shell_extract.py | 72 +++++- electrolytes/solvation_shell_extract_old.py | 255 -------------------- setup.py | 4 - 4 files changed, 68 insertions(+), 383 deletions(-) delete mode 100644 electrolytes/example_for_sanjeev.py delete mode 100644 electrolytes/solvation_shell_extract_old.py diff --git a/electrolytes/example_for_sanjeev.py b/electrolytes/example_for_sanjeev.py deleted file mode 100644 index cce420d..0000000 --- a/electrolytes/example_for_sanjeev.py +++ /dev/null @@ -1,120 +0,0 @@ -from schrodinger.structure import StructureReader -from schrodinger.structutils import analyze -import json - -# Read a structure -st = StructureReader.read("thing.mae") - -# Read json metadat file -with open("thing.json") as f: - metadata = json.load(f) - -# Get a molecule number -res = next((res for res in st.residue if res.pdbres == "AAA "), None) -if res is None: - mol_num = 1 -else: - mol_num = res.molecule_number - -# Extract entire residues (can also say fillmol if you prefer) within 3 angstroms of molecule 1 -ats = set(analyze.evaluate_asl(st, f"fillres within 3 mol {mol_num}")) -mol_included = [mol_num] - - -def get_extra_solutes(st, ats, radius, res_names, mol_included): - """ - Gets the molecule numbers of solute molecules that are within the radius - and not already included. - """ - extras = [] - for at in ats: - if st.atom[at].molecule_number in mol_included: - continue - if any(res_name == st.atom[at].getResidue().pdbres for res_name in res_names): - extras.append(st.atom[at].molecule_number) - return extras - - -extras = get_extra_solutes(st, ats, 3, ["AAA ", "BBB "], mol_included) -while extras: - ats.update( - analyze.evaluate_asl( - st, f'fillres within 3 mol {",".join([str(i) for i in extras])}' - ) - ) - mol_included.extend(extras) - if len(ats) < 200: - extras = get_extra_solutes(st, ats, 3, ["AAA ", "BBB "], mol_included) - else: - break -st2 = st.extract(sorted(ats), copy_props=True) -st2.write("thing2.mae") - -# Now do a random water near the box edge, molecule 91 -# label the molecule so we can keep track -for at in st.molecule[91].atom: - at.property["i_m_label"] = 1 -ats = analyze.evaluate_asl(st, "fillres within 3 mol 91") -st2 = st.extract(ats, copy_props=True) -st2.write("thing3.mae") - -# Oh no! Our system is broken across the PBC boundary. Let's tell it to contract -# everthing to be centered on our molecule of interest (this will also handle if -# a molecule is split across a PBC) -from schrodinger.application.matsci import clusterstruct - -mol_ats = [at.index for at in st2.atom if at.property.pop("i_m_label", None) == 1] -clusterstruct.contract_structure2(st2, contract_on_atoms=mol_ats) -st2.write("thing3b.mae") - -# Suppose we have several structures and we want to group them by conformers -from schrodinger.comparison import are_conformers -from schrodinger.application.jaguar.utils import group_items - - -def get_env_of_mol(st, mol_idx, radius): - st_copy = st.copy() - for at in st_copy.molecule[mol_idx].atom: - at.property["i_m_label"] = 1 - ats = analyze.evaluate_asl(st_copy, f"fillres within {radius} mol {mol_idx}") - st2 = st_copy.extract(ats, copy_props=True) - mol_ats = [at.index for at in st2.atom if at.property.pop("i_m_label", None) == 1] - clusterstruct.contract_structure2(st2, contract_on_atoms=mol_ats) - return st2 - - -st_list = [get_env_of_mol(st, i, 3) for i in range(2, 100)] - -grouped_items = group_items(st_list, are_conformers) -# we now have lists of lists of structures where each list of structures are conformers of each other - -from schrodinger.comparison.atom_mapper import ConnectivityAtomMapper -from schrodinger.structutils import rmsd - - -def renumber_molecules_to_match(mol_list): - """ - Ensure that topologically equivalent sites are equivalently numbered - """ - mapper = ConnectivityAtomMapper(use_chirality=False) - atlist = range(1, mol_list[0].atom_total + 1) - renumbered_mols = [mol_list[0]] - for mol in mol_list[1:]: - _, r_mol = mapper.reorder_structures(mol_list[0], atlist, mol, atlist) - renumbered_mols.append(r_mol) - return renumbered_mols - - -# Now we have ensured that topologically related atoms are equivalently numbered (up to molecular symmetry) -grouped_items = [renumber_molecules_to_match(items) for items in grouped_items] - -# example grouping -group = grouped_items[1] -# Compare all atoms for RMSD (remember that Schrodinger atoms/molecules are 1-indexed -at_list = list(range(1, group[0].atom_total + 1)) -# Note that this function will translate/rotate all structures to align with the first one -# If this is not desired, run function on a copy, e.g. other.copy() -rmsds = [ - rmsd.superimpose(group[0], at_list, other, at_list, use_symmetry=True) - for other in group[1:] -] diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index fa1bc49..26110d7 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -91,7 +91,7 @@ def extract_solvation_shells( if i > 10: # TODO: fix this break - # extract all atoms in this solute + # extract all solute molecules solute_molecules = [ res for res in st.residue if res.pdbres == f"{residue} " ] @@ -146,10 +146,74 @@ def extract_solvation_shells( # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) - # Now repeat for solvents: + # Now repeat for solvents to capture solvent-solvent interactions for species, residue in solvents.items(): - # TODO: implement - pass + logging.info(f"Extracting shells around {species})") + for radius in radii: + logging.info(f"Radius = {radius} A") + expanded_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + # assign partial charges to atoms + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + + if i > 10: # TODO: fix this + break + + # extract all solvent molecules + solvent_molecules = [ + res for res in st.residue if res.pdbres == f"{residue} " + ] + central_solvent_nums = [mol.molecule_number for mol in solute_molecules] + # Extract solvation shells containing entire residues within 3 angstroms of each molecule + # if only part of a residue is within the radius, include the whole thing + shells = [ + set( + analyze.evaluate_asl( + st, f"fillres within {radius} mol {mol_num}" + ) + ) + for mol_num in central_solute_nums + ] + + # Now expand the shells + for shell, central_solute in zip(shells, central_solute_nums): + expanded_shell = expand_shell( + st, + shell, + central_solute, + radius, + solute_resnames, + max_shell_size=200, + ) + expanded_shells.append(expanded_shell) + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + # TODO: speed this up + grouped_shells = group_with_comparison(expanded_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [ + renumber_molecules_to_match(items) for items in grouped_shells + ] + + # Now extract the top N most diverse shells from each group + logging.info(f"Extracting top {top_n} most diverse shells from each group") + final_shells = [] + # example grouping - set of structures + for shell_group in tqdm(grouped_shells): + filtered_shells = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered_shells) + + # Save the final shells + logging.info(f"Saving final solvation shells") + save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + # TODO: seems like this is saving an extra line at the end of the xyz files + st.write(os.path.join(save_path, f"shell_{i}.xyz")) if __name__ == "__main__": diff --git a/electrolytes/solvation_shell_extract_old.py b/electrolytes/solvation_shell_extract_old.py deleted file mode 100644 index 7c8e986..0000000 --- a/electrolytes/solvation_shell_extract_old.py +++ /dev/null @@ -1,255 +0,0 @@ -import os -import logging -import argparse -import random -import numpy as np -from tqdm import tqdm -from typing import List -from collections import defaultdict -import matplotlib.pyplot as plt -import MDAnalysis as mda -from solvation_analysis.solute import Solute -from solvation_analysis._column_names import FRAME, SOLUTE_IX -from pymatgen.core.structure import Molecule -from solvation_shell_utils import ( - filter_by_rmsd, - wrap_positions, - extract_charges_from_lammps_file, -) -from utils import parse_list_of_lists - - -def extract_solvation_shells( - input_dir: str, - save_dir: str, - system_name: str, - solute_atoms: List[str], - solvent_atoms: List[List[str]], - min_coord: int, - max_coord: int, - top_n: int, -): - """ - Given a MD trajectory in a PDB file, perform a solvation analysis - on the specified solute to extract the first solvation shell. For each coordination number in the specified range, - extract and save the top_n most diverse snapshots based on a RMSD criterion. - - Args: - input_dir: Path to 1) the PDB file containing the MD trajectory and 2) the LAMMPS file containing the initial structure (used to extract partial charges). - save_dir: Directory in which to save extracted solvation shells. - system_name: Name of the system - used for naming the save directory. - solute_atoms: List of names (in the PDB file) of the solute atom types (e.g NA0) with which to perform the solvation analysis. - solvent_atoms: List of names (in the PDB file) of the solvent atom types with which to perform the solvation analysis. - min_coord: Minimum coordination number to consider. - max_coord: Maximum coordination number to consider. - top_n: Number of snapshots to extract per coordination number. - """ - solute_atoms_name = " ".join(solute_atoms) - # Create save directory - os.makedirs(os.path.join(save_dir, system_name, solute_atoms_name), exist_ok=True) - - # Read charges from LAMMPS file - lammps_file_path = os.path.join(input_dir, "system.data") - charges = extract_charges_from_lammps_file(lammps_file_path) - - # Initialize MDA Universe - pdb_file_path = os.path.join(input_dir, "system_output.pdb") - universe = mda.Universe(pdb_file_path) - - # Add PBC box - with open(pdb_file_path) as file: - dimension_lines = file.readlines()[1] - a = float(dimension_lines.split()[1]) - b = float(dimension_lines.split()[2]) - c = float(dimension_lines.split()[3]) - universe.dimensions = [a, b, c, 90, 90, 90] - - lattices = np.array([a, b, c])[None][None] - - # Choose solute atom - # TODO: try to join multiple atoms in the same solute, doesn't currently work - solute_query = " or ".join(f"name {atom}" for atom in solute_atoms) - solute = universe.select_atoms(solute_query) - # other_query = " or ".join(f"name {atom}" for atom in other_solute_atoms) - # other_solu = universe.select_atoms(other_query) - - logging.info("Translating atoms to solute center of mass") - for ts in tqdm(universe.trajectory): - ts.dimensions = universe.dimensions - solu_center = solute.center_of_mass(wrap=True) - dim = ts.triclinic_dimensions - box_center = np.sum(dim, axis=0) / 2 - universe.atoms.translate(box_center - solu_center) - - universe.atoms.unwrap() - - # TODO: need to remove the other components of the solute from the solvent atoms? Doesn't matter since the other solute atom won't be close? - - # This doesn't handle multiple solvents - solvent = ( - universe.atoms - solute - ) # TODO: might need to count anything other than the solute of interest as a potential solvent - # TODO: set an upper cutoff for solute-solvent interactions - - solute_name = "".join(atom for atom in solute_atoms) - - logging.info("Running solvation analysis") - # Identify the cutoff for the first solvation shell, based on the MD trajectory - - # discovered that the reason the analysis was failing was because the default cutoff region of 6.5 was too small for the Cl04 anion - kernel_kwargs = {"cutoff_region": (1.5, 8)} - solv_anal = Solute.from_atoms( - solute, - {"solvent": solvent}, - solute_name=solute_name, - kernel_kwargs=kernel_kwargs, - ) - # TODO: subsample fewer solutes to speed up the analysis - - solv_anal.run() # which solute's radii is this using? - - max_radii = 0 - max_name = "" - for solute_name in solv_anal.atom_solutes.keys(): - radii = solv_anal.atom_solutes[solute_name].radii["solvent"] - if radii > max_radii: - max_radii = radii - max_name = solute_name - - # TODO: what do we do with this max or mean radii? Can we need to use it to re-run the analysis? - - # except AssertionError: - # logging.info("Failed to automatically find the radius, trying again with a heuristic radius") - # heuristic_radii = 2.5 # TODO: add heuristic radii based on effective sizes of solute and solvent - # solv_anal = Solute.from_atoms(solu, {"solvent": solvent}, solute_name = solute_name, radii={'solvent': heuristic_radii}) - # solv_anal.run() - - # Plot the RDF - solv_anal.plot_solvation_radius(max_name, "solvent") - plt.savefig( - os.path.join(save_dir, system_name, solute_atoms_name, "solvation_rdf.png") - ) - - # There's probably a much faster way to do this - # But for now, we're prototyping, so slow is okay - - # Store the solvation shells with different numbers of solvents (sorted from highest to lowest frequency) - shells = dict() - for j in solv_anal.speciation.speciation_fraction["solvent"]: - shells[j] = solv_anal.speciation.get_shells({"solvent": j}) - - # Now let's try getting the most diverse structures for each particular coordination number - # This is also a bit slow, particularly for the more common and/or larger solvent shells - - # TODO: instead of specifying a range of coordination numbers, we could specify the top n most common coordination numbers (but we also probably want to extract rare configurations) - for c in range(min_coord, max_coord + 1): - if c in shells.keys(): - logging.info( - f"Processing {len(shells[c])} shells with coordination number {c}" - ) - os.makedirs( - os.path.join(save_dir, system_name, solute_atoms_name, f"coord={c}"), - exist_ok=True, - ) - shell_species = [] - shell_positions = [] - # Extract the shell positions - - for i, (index, _) in tqdm(enumerate(shells[c].iterrows())): - universe.atoms.unwrap() - frame, solute_idx = index - shell = solv_anal.solvation_data.xs( - (frame, solute_idx), level=(FRAME, SOLUTE_IX) - ) - shell = solv_anal._df_to_atom_group(shell, solute_index=index[1]) - # TODO: assertion that compositions/element orderings are the same - if len(shell.atoms.elements) > len(shell_species): - shell_species = shell.atoms.elements - shell_positions.append(wrap_positions(shell.atoms.positions, lattices)) - if i > 1000: # TODO: don't hardcode this - break - - by_num_atoms = defaultdict(list) - for sps in shell_positions: - by_num_atoms[len(sps)].append(sps) - - # filter by number of atoms per shell - selections_by_num_atoms = { - num_atoms: filter_by_rmsd(shells_with_num_atoms, top_n) - for num_atoms, shells_with_num_atoms in by_num_atoms.items() - } - - for ( - shell_size, - shell_positions, - ) in selections_by_num_atoms.items(): # loop over sizes - for idx, shell_pos in enumerate(shell_positions): - if shell_pos.shape[0] == shell_species.shape[0]: - - # Save shell as xyz file - mol = Molecule( - shell_species, shell_pos, charge=round(sum(charges)) - ) - mol.to( - os.path.join( - save_dir, - system_name, - solute_atoms_name, - f"coord={c}", - f"size{shell_size}_selection{idx}.xyz", - ), - "xyz", - ) - - -if __name__ == "__main__": - logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) - random.seed(10) - - parser = argparse.ArgumentParser() - parser.add_argument( - "--input_dir", - type=str, - help="Path containing PDB trajectory and LAMMPS data files", - ) - parser.add_argument("--save_dir", type=str, help="Path to save xyz files") - parser.add_argument( - "--system_name", type=str, help="Name of system used for directory naming" - ) - parser.add_argument( - "--solute_atoms", - type=parse_list_of_lists, - help="Which solute atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", - ) - - parser.add_argument( - "--solvent_atoms", - type=parse_list_of_lists, - help="Which solvent atom(s) to extract solvation shells for (accepts a list of lists, where each list is separated by a semicolon: e.g., 'a,b,c;d,e,f')", - ) - - parser.add_argument( - "--min_coord", type=int, help="Minimum shell coordination number to extract" - ) - parser.add_argument( - "--max_coord", type=int, help="Maximum shell coordination number to extract" - ) - parser.add_argument( - "--top_n", - type=int, - default=20, - help="Number of most diverse shells to extract per coordination number", - ) - - args = parser.parse_args() - - extract_solvation_shells( - args.input_dir, - args.save_dir, - args.system_name, - args.solute_atoms, - args.solvent_atoms, - args.min_coord, - args.max_coord, - args.top_n, - ) diff --git a/setup.py b/setup.py index c17fb66..4963923 100644 --- a/setup.py +++ b/setup.py @@ -17,10 +17,6 @@ "quacc[sella]>=0.7.2", "numpy", "tqdm", - "rmsd", - "MDAnalysis", - "pymatgen", - "solvation-analysis", ], include_package_data=True, ) From 46aab0d86ce88ecf7a1522e78b38e69cf6d1863a Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 17:33:20 -0700 Subject: [PATCH 058/117] ignore readme --- .gitignore | 3 +++ electrolytes/README.md | 57 ------------------------------------------ 2 files changed, 3 insertions(+), 57 deletions(-) delete mode 100644 electrolytes/README.md diff --git a/.gitignore b/.gitignore index c650265..61755b7 100644 --- a/.gitignore +++ b/.gitignore @@ -125,4 +125,7 @@ maestro_package/ .ipynb_checkpoints/ *ipynb +# Misc +notes.txt + diff --git a/electrolytes/README.md b/electrolytes/README.md deleted file mode 100644 index 5d5a445..0000000 --- a/electrolytes/README.md +++ /dev/null @@ -1,57 +0,0 @@ -List of questions as of 5/30: - -1. Do we want to remove the other solutes (including counterion on the same solute) when doing the solvation analysis? -2. How to handle multiple solutes or solvents with the same atoms present? Can't just select by atom names - One Idea: Pass in a list of lists of solutes and solvents - how to automatically get this from the PDB or LAMMPS file? -3. How do we want to deal with coordination numbers? I.e. pick a defined min and max as we're doing currently, or pick the k most common coordination numbers? Or pick a set number from each type of coordination number? Over-sample the rare ones? -4. For the case of multiple solvents, not enough to split up shells by coordination number - need to also split up by number of each solvent. -5. What to do when it's only an ionic liquid (no solvent) - - -Notes from chatting with Evan: - -Maybe put ionic liquids on hold - -Focus on the case where we have one or more solutes and one or more solvents - -Compute average solvation radius over all atoms in the solute (or randomly sample a subset for larger solute molecules) - -Anything that isn't the solute under consideration needs to be defined as a separate solvent (with some cutoff to ensure that we don't have silly comparison e.g between two cations.) - -Save rdfs and rdf data/troughs, etc so that if needed, we can do a post-analysis with tabulaed radii - -For solvent-solvent interactions, try two approaches: -1. Same analysis code as with solutes, but just make the solvent a solute (may not work if there aren't clear RDFs for the solvent) -2. Pick random solvent molecules, pick a random radius with bounds determined by a solvent-dependent heuristic, sample shells, sort by composition, and pick most diverse - - - -Meeting on 6/7: - -Main problem with the current analysis pipeline is that there are different analysis approaches for low concentration, high concentration, ionic liquids, etc. Also unclear how to define radii for multi-atom solutes. This is going to be too slow. - -Maybe the simplest approach is to choose 2-3 heuristic radii (not system specific) around each solute and solvent and then bin them by composition/graph hash. - -How do we determine these radii? Go through a few sample pdb files with different cases (multi solute, multi solvent, ionic liquid, etc.) and then do some heuristic solvation analysis to find the radii. - -Question: when we expand a shell around a solute, if we run into another solute, do we also expand around that? Probably not needed because this will be captured in the next larger radius. - -Schrodinger has easy ways to do this. Sanjeev/Daniel sit down and work with Schrodinger to see if it solves all these problems. - -LAMMPS files from Muhammad need to have a mapping from atom to residue names and solute/solvent. Muhammad and Evan work on this together - - -Meeting of 6/11 with Daniel: -MGCF at Berkeley -Maestro for visualizing stuff - -Schrodinger easily accounts for different atom orderings (e.g permutations, etc.) and PBCs - - - - - - - - - From af2245bedb9197dd9bd91b261b6d555726e52022 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 19:03:04 -0700 Subject: [PATCH 059/117] begin solvent-solvent stuff, not working --- electrolytes/solvation_shell_extract.py | 228 ++++++++++++++---------- electrolytes/solvation_shell_utils.py | 43 +++-- 2 files changed, 160 insertions(+), 111 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 26110d7..2a52372 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -16,9 +16,11 @@ expand_shell, renumber_molecules_to_match, filter_by_rmsd, + filter_shells_with_solute_atoms, ) from utils import validate_metadata_file from schrodinger.comparison import are_conformers +from schrodinger.application.matsci import clusterstruct from schrodinger.application.jaguar.utils import group_with_comparison from schrodinger.structutils import rmsd @@ -27,7 +29,8 @@ def extract_solvation_shells( input_dir: str, save_dir: str, system_name: str, - radii: List[float], + solute_radii: List[float], + solvent_radii: List[float], top_n: int, ): """ @@ -38,7 +41,8 @@ def extract_solvation_shells( input_dir: Path to 1) the PDB file containing the MD trajectory (system_output.pdb) and 2) a metadata file (system_metadata.json) save_dir: Directory in which to save extracted solvation shells. system_name: Name of the system - used for naming the save directory. - radii: List of solvation shell radii to extract. + solute_radii: List of shell radii to extract around solutes. + solvent_radii: List of shell radii to extract around solvents. top_n: Number of snapshots to extract per topology. """ @@ -78,80 +82,91 @@ def extract_solvation_shells( # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin - for species, residue in solutes.items(): - logging.info(f"Extracting solvation shells around {species})") - for radius in radii: - logging.info(f"Radius = {radius} A") - expanded_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps - # assign partial charges to atoms - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge - - if i > 10: # TODO: fix this - break - - # extract all solute molecules - solute_molecules = [ - res for res in st.residue if res.pdbres == f"{residue} " - ] - central_solute_nums = [mol.molecule_number for mol in solute_molecules] - # Extract solvation shells containing entire residues within 3 angstroms of each molecule - # if only part of a residue is within the radius, include the whole thing - shells = [ - set( - analyze.evaluate_asl( - st, f"fillres within {radius} mol {mol_num}" - ) - ) - for mol_num in central_solute_nums - ] - - # Now expand the shells - for shell, central_solute in zip(shells, central_solute_nums): - expanded_shell = expand_shell( - st, - shell, - central_solute, - radius, - solute_resnames, - max_shell_size=200, - ) - expanded_shells.append(expanded_shell) - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - # TODO: speed this up - grouped_shells = group_with_comparison(expanded_shells, are_conformers) - - # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - grouped_shells = [ - renumber_molecules_to_match(items) for items in grouped_shells - ] - - # Now extract the top N most diverse shells from each group - logging.info(f"Extracting top {top_n} most diverse shells from each group") - final_shells = [] - # example grouping - set of structures - for shell_group in tqdm(grouped_shells): - filtered_shells = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(filtered_shells) - - # Save the final shells - logging.info(f"Saving final solvation shells") - save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") - os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): - # TODO: seems like this is saving an extra line at the end of the xyz files - st.write(os.path.join(save_path, f"shell_{i}.xyz")) + # for species, residue in solutes.items(): + # logging.info(f"Extracting solvation shells around {species}") + # for radius in solute_radii: + # logging.info(f"Radius = {radius} A") + # expanded_shells = [] + # for i, st in tqdm(enumerate(structures)): # loop over timesteps + # # assign partial charges to atoms + # for at, charge in zip(st.atom, partial_charges): + # at.partial_charge = charge + + # if i > 10: # TODO: fix this + # break + + # # extract all solute molecules + # solute_molecules = [ + # res for res in st.residue if res.pdbres == f"{residue} " + # ] + # central_solute_nums = [mol.molecule_number for mol in solute_molecules] + # # Extract solvation shells + # shells = [ + # set( + # analyze.evaluate_asl( + # st, f"fillres within {radius} mol {mol_num}" + # ) + # ) + # for mol_num in central_solute_nums + # ] + + # # Now expand the shells: + # # TODO: this is slow, speed it up + # for shell, central_solute in zip(shells, central_solute_nums): + # expanded_shell = expand_shell( + # st, + # shell, + # central_solute, + # radius, + # solute_resnames, + # max_shell_size=200, + # ) + # expanded_structure = st.extract(expanded_shell, copy_props=True) + + # # find index of central solute in the expanded_shell (adjust for 1-indexing) + # central_solute_idx = expanded_shell.index(central_solute) + 1 + + # # contract everthing to be centered on our molecule of interest + # # (this will also handle if a molecule is split across a PBC) + # clusterstruct.contract_structure2( + # expanded_structure, contract_on_atoms=[central_solute_idx] + # ) + + # expanded_shells.append(expanded_structure) + + # # Now compare the expanded shells and group them by similarity + # # we will get lists of lists of shells where each list of structures are conformers of each other + # logging.info("Grouping solvation shells into conformers") + # # TODO: speed this up + # grouped_shells = group_with_comparison(expanded_shells, are_conformers) + + # # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + # grouped_shells = [ + # renumber_molecules_to_match(items) for items in grouped_shells + # ] + + # # Now extract the top N most diverse shells from each group + # logging.info(f"Extracting top {top_n} most diverse shells from each group") + # final_shells = [] + # # example grouping - set of structures + # for shell_group in tqdm(grouped_shells): + # filtered = filter_by_rmsd(shell_group, n=top_n) + # final_shells.extend(filtered) + + # # Save the final shells + # logging.info(f"Saving final shells") + # save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + # os.makedirs(save_path, exist_ok=True) + # for i, st in enumerate(final_shells): + # # TODO: seems like this is saving an extra line at the end of the xyz files + # st.write(os.path.join(save_path, f"shell_{i}.xyz")) # Now repeat for solvents to capture solvent-solvent interactions for species, residue in solvents.items(): - logging.info(f"Extracting shells around {species})") - for radius in radii: + logging.info(f"Extracting shells around {species}") + for radius in solvent_radii: logging.info(f"Radius = {radius} A") - expanded_shells = [] + filtered_shells = [] for i, st in tqdm(enumerate(structures)): # loop over timesteps # assign partial charges to atoms for at, charge in zip(st.atom, partial_charges): @@ -164,36 +179,51 @@ def extract_solvation_shells( solvent_molecules = [ res for res in st.residue if res.pdbres == f"{residue} " ] - central_solvent_nums = [mol.molecule_number for mol in solute_molecules] - # Extract solvation shells containing entire residues within 3 angstroms of each molecule - # if only part of a residue is within the radius, include the whole thing + central_solvent_nums = [ + mol.molecule_number for mol in solvent_molecules + ] + + # Extract solvation shells shells = [ set( analyze.evaluate_asl( st, f"fillres within {radius} mol {mol_num}" ) ) - for mol_num in central_solute_nums + for mol_num in central_solvent_nums ] - - # Now expand the shells - for shell, central_solute in zip(shells, central_solute_nums): - expanded_shell = expand_shell( - st, - shell, - central_solute, - radius, - solute_resnames, - max_shell_size=200, + # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell + for shell, central_solvent in zip(shells, central_solvent_nums): + if central_solvent not in shell: + shell.add(central_solvent) + + # Only keep the shells that have no solute atoms + import pdb; pdb.set_trace() + filtered = filter_shells_with_solute_atoms(shells, st, solute_resnames) + filtered_structures = [st.extract(shell, copy_props=True) for shell in filtered] + + # Now contract the shells to be centered on the central solvent atom + # TODO: verify that this in place operation is correct + for shell, central_solvent_idx in zip(filtered, central_solvent_nums): + central_solvent_idx = shell.index(central_solvent_idx) + 1 + clusterstruct.contract_structure2( + shell, contract_on_atoms=[central_solvent_idx] ) - expanded_shells.append(expanded_shell) + filtered_shells.extend(filtered_structures) + + # Choose a random subset of shells + assert len(filtered_shells) > 0, "No solute-free shells found for solvent" + random.shuffle(filtered_shells) + filtered_shells = filtered_shells[:1000] #TODO: don't hardcode this + + # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") # TODO: speed this up - grouped_shells = group_with_comparison(expanded_shells, are_conformers) - + grouped_shells = group_with_comparison(filtered_shells, are_conformers) + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [ renumber_molecules_to_match(items) for items in grouped_shells @@ -204,11 +234,11 @@ def extract_solvation_shells( final_shells = [] # example grouping - set of structures for shell_group in tqdm(grouped_shells): - filtered_shells = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(filtered_shells) + filtered = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered) # Save the final shells - logging.info(f"Saving final solvation shells") + logging.info(f"Saving final shells") save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") os.makedirs(save_path, exist_ok=True) for i, st in enumerate(final_shells): @@ -232,10 +262,17 @@ def extract_solvation_shells( ) parser.add_argument( - "--radii", + "--solute_radii", + type=list, + default=[3], + help="List of shell radii to extract around solutes", + ) + + parser.add_argument( + "--solvent_radii", type=list, default=[3], - help="List of solvation shell radii to extract", + help="List of shell radii to extract around solvents", ) parser.add_argument( @@ -251,6 +288,7 @@ def extract_solvation_shells( args.input_dir, args.save_dir, args.system_name, - args.radii, + args.solute_radii, + args.solvent_radii, args.top_n, ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 68f5e55..323d7f9 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -12,14 +12,35 @@ from schrodinger.structure import Structure +def filter_shells_with_solute_atoms( + shells: List[Set[int]], st: Structure, solute_res_names: List[str] +) -> List[List[int]]: + """ + Filter out shells that contain solute atoms. + Args: + shells: List of sets of atom indices (1-indexed) that correspond to shells + st: Entire structure from the PDB file + solute_res_names: List of residue names that correspond to solute atoms in the simulation + Returns: + List of sets of atom indices (1-indexed) that correspond to shells without solute atoms + """ + actual_shells = [st.extract(shell, copy_props=True) for shell in shells] + filtered_shells = [ + shell + for shell, actual_shell in zip(shells, actual_shells) + if not any(at.getResidue().pdbres.strip() in solute_res_names for at in actual_shell.atom) + ] + return filtered_shells + + def expand_shell( st: Structure, shell_ats: Set[int], central_solute: int, radius: float, solute_res_names: List[str], - max_shell_size: int = 200, -) -> Structure: + max_shell_size: int = 100, +) -> List[int]: """ Expands a solvation shell. If there are any (non-central) solutes present in the shell, recursively include shells around those solutes. @@ -33,7 +54,7 @@ def expand_shell( solute_res_names: List of residue names that correspond to solute atoms in the simulation max_shell_size: Maximum size (in atoms) of the expanded shell Returns: - Structure object containing the expanded solvation shell + Sorted list of atoms containing the expanded solvation shell (1-indexed) """ # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell if central_solute not in shell_ats: @@ -46,7 +67,7 @@ def expand_shell( # atom is part of a non-central solute molecule - should expand the shell if ( st.atom[at].molecule_number not in solutes_included - and st.atom[at].getResidue().pdbres in solute_res_names + and st.atom[at].getResidue().pdbres.strip() in solute_res_names ): new_solutes.add(st.atom[at].molecule_number) @@ -61,19 +82,9 @@ def expand_shell( solutes_included.update(new_solutes) else: break + # TODO: should we return a list instead of a set? shell_ats = sorted(shell_ats) - final_structure = st.extract(shell_ats, copy_props=True) - - # find index of central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_idx = shell_ats.index(central_solute) + 1 - - # contract everthing to be centered on our molecule of interest - # (this will also handle if a molecule is split across a PBC) - - clusterstruct.contract_structure2( - final_structure, contract_on_atoms=[central_solute_idx] - ) - return final_structure + return shell_ats def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: From e0479bec534c2cc71ff45b25a49a8b04d519d850 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 19:12:44 -0700 Subject: [PATCH 060/117] revert to working solvent-solvent interactions, need to implement PBCs --- electrolytes/solvation_shell_extract.py | 206 ++++++++++-------------- electrolytes/solvation_shell_utils.py | 32 ++-- 2 files changed, 111 insertions(+), 127 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 2a52372..2cd8348 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -20,7 +20,6 @@ ) from utils import validate_metadata_file from schrodinger.comparison import are_conformers -from schrodinger.application.matsci import clusterstruct from schrodinger.application.jaguar.utils import group_with_comparison from schrodinger.structutils import rmsd @@ -82,11 +81,79 @@ def extract_solvation_shells( # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin - # for species, residue in solutes.items(): - # logging.info(f"Extracting solvation shells around {species}") - # for radius in solute_radii: + for species, residue in solutes.items(): + logging.info(f"Extracting solvation shells around {species}") + for radius in solute_radii: + logging.info(f"Radius = {radius} A") + expanded_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + # assign partial charges to atoms + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + + if i > 10: # TODO: fix this + break + + # extract all solute molecules + solute_molecules = [ + res for res in st.residue if res.pdbres.strip() == f"{residue}" + ] + central_solute_nums = [mol.molecule_number for mol in solute_molecules] + # Extract solvation shells + shells = [ + set( + analyze.evaluate_asl( + st, f"fillres within {radius} mol {mol_num}" + ) + ) + for mol_num in central_solute_nums + ] + + # Now expand the shells + for shell, central_solute in zip(shells, central_solute_nums): + expanded_shell = expand_shell( + st, + shell, + central_solute, + radius, + solute_resnames, + max_shell_size=200, + ) + expanded_shells.append(expanded_shell) + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + # TODO: speed this up + grouped_shells = group_with_comparison(expanded_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [ + renumber_molecules_to_match(items) for items in grouped_shells + ] + + # Now extract the top N most diverse shells from each group + logging.info(f"Extracting top {top_n} most diverse shells from each group") + final_shells = [] + # example grouping - set of structures + for shell_group in tqdm(grouped_shells): + filtered = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered) + + # Save the final shells + logging.info(f"Saving final shells") + save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + # TODO: seems like this is saving an extra line at the end of the xyz files + st.write(os.path.join(save_path, f"shell_{i}.xyz")) + + # # Now repeat for solvents to capture solvent-solvent interactions + # for species, residue in solvents.items(): + # logging.info(f"Extracting shells around {species}") + # for radius in solvent_radii: # logging.info(f"Radius = {radius} A") - # expanded_shells = [] + # filtered_shells = [] # for i, st in tqdm(enumerate(structures)): # loop over timesteps # # assign partial charges to atoms # for at, charge in zip(st.atom, partial_charges): @@ -95,11 +162,14 @@ def extract_solvation_shells( # if i > 10: # TODO: fix this # break - # # extract all solute molecules - # solute_molecules = [ - # res for res in st.residue if res.pdbres == f"{residue} " + # # extract all solvent molecules + # solvent_molecules = [ + # res for res in st.residue if res.pdbres.strip() == f"{residue}" + # ] + # central_solvent_nums = [ + # mol.molecule_number for mol in solvent_molecules # ] - # central_solute_nums = [mol.molecule_number for mol in solute_molecules] + # # Extract solvation shells # shells = [ # set( @@ -107,38 +177,24 @@ def extract_solvation_shells( # st, f"fillres within {radius} mol {mol_num}" # ) # ) - # for mol_num in central_solute_nums + # for mol_num in central_solvent_nums # ] - # # Now expand the shells: - # # TODO: this is slow, speed it up - # for shell, central_solute in zip(shells, central_solute_nums): - # expanded_shell = expand_shell( - # st, - # shell, - # central_solute, - # radius, - # solute_resnames, - # max_shell_size=200, - # ) - # expanded_structure = st.extract(expanded_shell, copy_props=True) + # # Only keep the shells that have no solute atoms + # filtered_shells.extend( + # filter_shells_with_solute_atoms(shells, st, solute_resnames) + # ) - # # find index of central solute in the expanded_shell (adjust for 1-indexing) - # central_solute_idx = expanded_shell.index(central_solute) + 1 - - # # contract everthing to be centered on our molecule of interest - # # (this will also handle if a molecule is split across a PBC) - # clusterstruct.contract_structure2( - # expanded_structure, contract_on_atoms=[central_solute_idx] - # ) - - # expanded_shells.append(expanded_structure) + # # Choose a random subset of shells + # assert len(filtered_shells) > 0, "No solute-free shells found for solvent" + # random.shuffle(filtered_shells) + # filtered_shells = filtered_shells[:1000] # # Now compare the expanded shells and group them by similarity # # we will get lists of lists of shells where each list of structures are conformers of each other # logging.info("Grouping solvation shells into conformers") # # TODO: speed this up - # grouped_shells = group_with_comparison(expanded_shells, are_conformers) + # grouped_shells = group_with_comparison(filtered_shells, are_conformers) # # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) # grouped_shells = [ @@ -161,90 +217,6 @@ def extract_solvation_shells( # # TODO: seems like this is saving an extra line at the end of the xyz files # st.write(os.path.join(save_path, f"shell_{i}.xyz")) - # Now repeat for solvents to capture solvent-solvent interactions - for species, residue in solvents.items(): - logging.info(f"Extracting shells around {species}") - for radius in solvent_radii: - logging.info(f"Radius = {radius} A") - filtered_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps - # assign partial charges to atoms - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge - - if i > 10: # TODO: fix this - break - - # extract all solvent molecules - solvent_molecules = [ - res for res in st.residue if res.pdbres == f"{residue} " - ] - central_solvent_nums = [ - mol.molecule_number for mol in solvent_molecules - ] - - # Extract solvation shells - shells = [ - set( - analyze.evaluate_asl( - st, f"fillres within {radius} mol {mol_num}" - ) - ) - for mol_num in central_solvent_nums - ] - # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell - for shell, central_solvent in zip(shells, central_solvent_nums): - if central_solvent not in shell: - shell.add(central_solvent) - - # Only keep the shells that have no solute atoms - import pdb; pdb.set_trace() - filtered = filter_shells_with_solute_atoms(shells, st, solute_resnames) - filtered_structures = [st.extract(shell, copy_props=True) for shell in filtered] - - # Now contract the shells to be centered on the central solvent atom - # TODO: verify that this in place operation is correct - for shell, central_solvent_idx in zip(filtered, central_solvent_nums): - central_solvent_idx = shell.index(central_solvent_idx) + 1 - clusterstruct.contract_structure2( - shell, contract_on_atoms=[central_solvent_idx] - ) - - filtered_shells.extend(filtered_structures) - - # Choose a random subset of shells - assert len(filtered_shells) > 0, "No solute-free shells found for solvent" - random.shuffle(filtered_shells) - filtered_shells = filtered_shells[:1000] #TODO: don't hardcode this - - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - # TODO: speed this up - grouped_shells = group_with_comparison(filtered_shells, are_conformers) - - # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - grouped_shells = [ - renumber_molecules_to_match(items) for items in grouped_shells - ] - - # Now extract the top N most diverse shells from each group - logging.info(f"Extracting top {top_n} most diverse shells from each group") - final_shells = [] - # example grouping - set of structures - for shell_group in tqdm(grouped_shells): - filtered = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(filtered) - - # Save the final shells - logging.info(f"Saving final shells") - save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") - os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): - # TODO: seems like this is saving an extra line at the end of the xyz files - st.write(os.path.join(save_path, f"shell_{i}.xyz")) - if __name__ == "__main__": logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 323d7f9..864d653 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -14,21 +14,23 @@ def filter_shells_with_solute_atoms( shells: List[Set[int]], st: Structure, solute_res_names: List[str] -) -> List[List[int]]: +) -> List[Structure]: """ Filter out shells that contain solute atoms. Args: - shells: List of sets of atom indices (1-indexed) that correspond to shells + shells: List of sets of atom indices that correspond to shells st: Entire structure from the PDB file solute_res_names: List of residue names that correspond to solute atoms in the simulation Returns: - List of sets of atom indices (1-indexed) that correspond to shells without solute atoms + List of Schrodinger structures that do not contain solute atoms """ actual_shells = [st.extract(shell, copy_props=True) for shell in shells] filtered_shells = [ shell - for shell, actual_shell in zip(shells, actual_shells) - if not any(at.getResidue().pdbres.strip() in solute_res_names for at in actual_shell.atom) + for shell in actual_shells + if not any( + at.getResidue().pdbres.strip() in solute_res_names for at in shell.atom + ) ] return filtered_shells @@ -39,8 +41,8 @@ def expand_shell( central_solute: int, radius: float, solute_res_names: List[str], - max_shell_size: int = 100, -) -> List[int]: + max_shell_size: int = 200, +) -> Structure: """ Expands a solvation shell. If there are any (non-central) solutes present in the shell, recursively include shells around those solutes. @@ -54,7 +56,7 @@ def expand_shell( solute_res_names: List of residue names that correspond to solute atoms in the simulation max_shell_size: Maximum size (in atoms) of the expanded shell Returns: - Sorted list of atoms containing the expanded solvation shell (1-indexed) + Structure object containing the expanded solvation shell """ # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell if central_solute not in shell_ats: @@ -82,9 +84,19 @@ def expand_shell( solutes_included.update(new_solutes) else: break - # TODO: should we return a list instead of a set? shell_ats = sorted(shell_ats) - return shell_ats + final_structure = st.extract(shell_ats, copy_props=True) + + # find index of central solute in the sorted shell_ats (adjust for 1-indexing) + central_solute_idx = shell_ats.index(central_solute) + 1 + + # contract everthing to be centered on our molecule of interest + # (this will also handle if a molecule is split across a PBC) + + clusterstruct.contract_structure2( + final_structure, contract_on_atoms=[central_solute_idx] + ) + return final_structure def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: From 9bc0a70454c4741ec5637c2f2fae1c8e99a27edd Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Mon, 1 Jul 2024 19:13:38 -0700 Subject: [PATCH 061/117] uncomment solvent part --- electrolytes/solvation_shell_extract.py | 136 ++++++++++++------------ 1 file changed, 68 insertions(+), 68 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 2cd8348..ba724e3 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -148,74 +148,74 @@ def extract_solvation_shells( # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) - # # Now repeat for solvents to capture solvent-solvent interactions - # for species, residue in solvents.items(): - # logging.info(f"Extracting shells around {species}") - # for radius in solvent_radii: - # logging.info(f"Radius = {radius} A") - # filtered_shells = [] - # for i, st in tqdm(enumerate(structures)): # loop over timesteps - # # assign partial charges to atoms - # for at, charge in zip(st.atom, partial_charges): - # at.partial_charge = charge - - # if i > 10: # TODO: fix this - # break - - # # extract all solvent molecules - # solvent_molecules = [ - # res for res in st.residue if res.pdbres.strip() == f"{residue}" - # ] - # central_solvent_nums = [ - # mol.molecule_number for mol in solvent_molecules - # ] - - # # Extract solvation shells - # shells = [ - # set( - # analyze.evaluate_asl( - # st, f"fillres within {radius} mol {mol_num}" - # ) - # ) - # for mol_num in central_solvent_nums - # ] - - # # Only keep the shells that have no solute atoms - # filtered_shells.extend( - # filter_shells_with_solute_atoms(shells, st, solute_resnames) - # ) - - # # Choose a random subset of shells - # assert len(filtered_shells) > 0, "No solute-free shells found for solvent" - # random.shuffle(filtered_shells) - # filtered_shells = filtered_shells[:1000] - - # # Now compare the expanded shells and group them by similarity - # # we will get lists of lists of shells where each list of structures are conformers of each other - # logging.info("Grouping solvation shells into conformers") - # # TODO: speed this up - # grouped_shells = group_with_comparison(filtered_shells, are_conformers) - - # # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - # grouped_shells = [ - # renumber_molecules_to_match(items) for items in grouped_shells - # ] - - # # Now extract the top N most diverse shells from each group - # logging.info(f"Extracting top {top_n} most diverse shells from each group") - # final_shells = [] - # # example grouping - set of structures - # for shell_group in tqdm(grouped_shells): - # filtered = filter_by_rmsd(shell_group, n=top_n) - # final_shells.extend(filtered) - - # # Save the final shells - # logging.info(f"Saving final shells") - # save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") - # os.makedirs(save_path, exist_ok=True) - # for i, st in enumerate(final_shells): - # # TODO: seems like this is saving an extra line at the end of the xyz files - # st.write(os.path.join(save_path, f"shell_{i}.xyz")) + # Now repeat for solvents to capture solvent-solvent interactions + for species, residue in solvents.items(): + logging.info(f"Extracting shells around {species}") + for radius in solvent_radii: + logging.info(f"Radius = {radius} A") + filtered_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + # assign partial charges to atoms + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + + if i > 10: # TODO: fix this + break + + # extract all solvent molecules + solvent_molecules = [ + res for res in st.residue if res.pdbres.strip() == f"{residue}" + ] + central_solvent_nums = [ + mol.molecule_number for mol in solvent_molecules + ] + + # Extract solvation shells + shells = [ + set( + analyze.evaluate_asl( + st, f"fillres within {radius} mol {mol_num}" + ) + ) + for mol_num in central_solvent_nums + ] + + # Only keep the shells that have no solute atoms + filtered_shells.extend( + filter_shells_with_solute_atoms(shells, st, solute_resnames) + ) + + # Choose a random subset of shells + assert len(filtered_shells) > 0, "No solute-free shells found for solvent" + random.shuffle(filtered_shells) + filtered_shells = filtered_shells[:1000] + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + # TODO: speed this up + grouped_shells = group_with_comparison(filtered_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [ + renumber_molecules_to_match(items) for items in grouped_shells + ] + + # Now extract the top N most diverse shells from each group + logging.info(f"Extracting top {top_n} most diverse shells from each group") + final_shells = [] + # example grouping - set of structures + for shell_group in tqdm(grouped_shells): + filtered = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered) + + # Save the final shells + logging.info(f"Saving final shells") + save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + # TODO: seems like this is saving an extra line at the end of the xyz files + st.write(os.path.join(save_path, f"shell_{i}.xyz")) if __name__ == "__main__": From e31bf227d093d89df6a700f6c362aabe5a7404f2 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 10:52:45 -0700 Subject: [PATCH 062/117] switch to superimpose version of rmsd --- electrolytes/solvation_shell_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 864d653..40b8bc7 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -136,7 +136,7 @@ def rmsd_wrapper(st1: Structure, st2: Structure) -> float: if st1 == st2: return 0.0 at_list = list(range(1, st1.atom_total + 1)) - return rmsd.calculate_in_place_rmsd(st1, at_list, st2, at_list, use_symmetry=True) + return rmsd.superimpose(st1, at_list, st2.copy(), at_list, use_symmetry=True) def renumber_molecules_to_match(mol_list): From 3ee9aa0e60a1471d25aedf4165c30f1b859f3742 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 11:14:55 -0700 Subject: [PATCH 063/117] make size checking caps hard --- electrolytes/solvation_shell_extract.py | 26 ++++++++++++++++++++++--- electrolytes/solvation_shell_utils.py | 17 ++++++++++++++++ 2 files changed, 40 insertions(+), 3 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index ba724e3..2f0e3c9 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -17,6 +17,7 @@ renumber_molecules_to_match, filter_by_rmsd, filter_shells_with_solute_atoms, + filter_shells_by_size, ) from utils import validate_metadata_file from schrodinger.comparison import are_conformers @@ -30,6 +31,7 @@ def extract_solvation_shells( system_name: str, solute_radii: List[float], solvent_radii: List[float], + max_shell_size: int, top_n: int, ): """ @@ -42,6 +44,7 @@ def extract_solvation_shells( system_name: Name of the system - used for naming the save directory. solute_radii: List of shell radii to extract around solutes. solvent_radii: List of shell radii to extract around solvents. + max_shell_size: Maximum size (in atoms) of saved shells. top_n: Number of snapshots to extract per topology. """ @@ -117,8 +120,11 @@ def extract_solvation_shells( central_solute, radius, solute_resnames, - max_shell_size=200, + max_shell_size=max_shell_size, ) + assert ( + expanded_shell.atom_total <= max_shell_size + ), "Expanded shell too large" expanded_shells.append(expanded_shell) # Now compare the expanded shells and group them by similarity @@ -180,13 +186,19 @@ def extract_solvation_shells( for mol_num in central_solvent_nums ] - # Only keep the shells that have no solute atoms + # Only keep the shells that have no solute atoms and below a maximum size filtered_shells.extend( - filter_shells_with_solute_atoms(shells, st, solute_resnames) + filter_shells_by_size( + filter_shells_with_solute_atoms(shells, st, solute_resnames), + max_shell_size, + ) ) # Choose a random subset of shells assert len(filtered_shells) > 0, "No solute-free shells found for solvent" + # check that every shell is below the max size + for shell in filtered_shells: + assert shell.atom_total <= max_shell_size, "Expanded shell too large" random.shuffle(filtered_shells) filtered_shells = filtered_shells[:1000] @@ -247,6 +259,13 @@ def extract_solvation_shells( help="List of shell radii to extract around solvents", ) + parser.add_argument( + "--max_shell_size", + type=int, + default=200, + help="Maximum size (in atoms) of the saved shells", + ) + parser.add_argument( "--top_n", type=int, @@ -262,5 +281,6 @@ def extract_solvation_shells( args.system_name, args.solute_radii, args.solvent_radii, + args.max_shell_size, args.top_n, ) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 40b8bc7..ddbd61d 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -12,6 +12,20 @@ from schrodinger.structure import Structure +def filter_shells_by_size( + shells: List[Structure], max_shell_size: int = 200 +) -> List[Structure]: + """ + Filter out shells that are larger than a certain size. + Args: + shells: List of shell structures + max_shell_size: Maximum size (in atoms) of the shell + Returns: + List of structures that correspond to shells that are smaller than max_size + """ + return [shell for shell in shells if shell.atom_total <= max_shell_size] + + def filter_shells_with_solute_atoms( shells: List[Set[int]], st: Structure, solute_res_names: List[str] ) -> List[Structure]: @@ -64,6 +78,7 @@ def expand_shell( solutes_included = set([central_solute]) while len(shell_ats) < max_shell_size: + old_shell_ats = shell_ats.copy() new_solutes = set() for at in shell_ats: # atom is part of a non-central solute molecule - should expand the shell @@ -84,6 +99,8 @@ def expand_shell( solutes_included.update(new_solutes) else: break + + shell_ats = old_shell_ats shell_ats = sorted(shell_ats) final_structure = st.extract(shell_ats, copy_props=True) From 8e2a1e07b7e5e4426795f5428f39576e239e0b94 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 13:15:06 -0700 Subject: [PATCH 064/117] address some more pr comments - more accurate comments, restructuring solute and solvent resname dictionary construction --- electrolytes/solvation_shell_extract.py | 32 ++++++++++--------------- electrolytes/solvation_shell_utils.py | 9 ++++--- 2 files changed, 17 insertions(+), 24 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 2f0e3c9..5c1fbf7 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -60,23 +60,17 @@ def extract_solvation_shells( partial_charges = np.array(metadata["partial_charges"]) - solutes = { - species: res - for res, species, type in zip( - metadata["residue"], metadata["species"], metadata["solute_or_solvent"] - ) - if type == "solute" - } # {species: residue name} mapping - solute_resnames = list(solutes.values()) - - solvents = { - species: res - for res, species, type in zip( - metadata["residue"], metadata["species"], metadata["solute_or_solvent"] - ) - if type == "solvent" - } # {species: residue name} mapping - solvent_resnames = list(solvents.values()) + solutes = {} + solvents = {} + for res, species, type in zip( + metadata["residue"], metadata["species"], metadata["solute_or_solvent"] + ): + if type == "solute": + solutes[species] = res + elif type == "solvent": + solvents[species] = res + solute_resnames = set(solutes.values()) + solvent_resnames = set(solvents.values()) # Read a structure structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) @@ -99,7 +93,7 @@ def extract_solvation_shells( # extract all solute molecules solute_molecules = [ - res for res in st.residue if res.pdbres.strip() == f"{residue}" + res for res in st.residue if res.pdbres.strip() == residue ] central_solute_nums = [mol.molecule_number for mol in solute_molecules] # Extract solvation shells @@ -170,7 +164,7 @@ def extract_solvation_shells( # extract all solvent molecules solvent_molecules = [ - res for res in st.residue if res.pdbres.strip() == f"{residue}" + res for res in st.residue if res.pdbres.strip() == residue ] central_solvent_nums = [ mol.molecule_number for mol in solvent_molecules diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index ddbd61d..ba0b69e 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -64,8 +64,8 @@ def expand_shell( and not already expanded around. Then, continuously expand around them as long as we don't hit an atom limit. Args: st: Entire structure from the PDB file - shell_ats: Set of atoms in a shell (1-indexed) - central_solute: Index of the central solute atom in the shell + shell_ats: Set of atom indices (of `st`) in a shell (1-indexed) + central_solute: Molecule index (of 'st') of the central solute in the shell radius: Solvation radius (Angstroms) to consider solute_res_names: List of residue names that correspond to solute atoms in the simulation max_shell_size: Maximum size (in atoms) of the expanded shell @@ -73,15 +73,14 @@ def expand_shell( Structure object containing the expanded solvation shell """ # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell - if central_solute not in shell_ats: - shell_ats.add(central_solute) + shell_ats.add(central_solute) solutes_included = set([central_solute]) while len(shell_ats) < max_shell_size: old_shell_ats = shell_ats.copy() new_solutes = set() for at in shell_ats: - # atom is part of a non-central solute molecule - should expand the shell + # If atom is part of a non-central solute molecule - should expand the shell if ( st.atom[at].molecule_number not in solutes_included and st.atom[at].getResidue().pdbres.strip() in solute_res_names From b2b836de7fb772c7a438d6541a0ce2e94c10b8ac Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 13:23:43 -0700 Subject: [PATCH 065/117] option to skip solvent centered shells --- electrolytes/solvation_shell_extract.py | 167 ++++++++++++++---------- 1 file changed, 97 insertions(+), 70 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 5c1fbf7..614b0b7 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -30,6 +30,7 @@ def extract_solvation_shells( save_dir: str, system_name: str, solute_radii: List[float], + skip_solvent_centered_shells: bool, solvent_radii: List[float], max_shell_size: int, top_n: int, @@ -43,6 +44,7 @@ def extract_solvation_shells( save_dir: Directory in which to save extracted solvation shells. system_name: Name of the system - used for naming the save directory. solute_radii: List of shell radii to extract around solutes. + skip_solvent_centered_shells: Skip extracting solvent-centered shells. solvent_radii: List of shell radii to extract around solvents. max_shell_size: Maximum size (in atoms) of saved shells. top_n: Number of snapshots to extract per topology. @@ -148,87 +150,103 @@ def extract_solvation_shells( # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) - # Now repeat for solvents to capture solvent-solvent interactions - for species, residue in solvents.items(): - logging.info(f"Extracting shells around {species}") - for radius in solvent_radii: - logging.info(f"Radius = {radius} A") - filtered_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps - # assign partial charges to atoms - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge - - if i > 10: # TODO: fix this - break - - # extract all solvent molecules - solvent_molecules = [ - res for res in st.residue if res.pdbres.strip() == residue - ] - central_solvent_nums = [ - mol.molecule_number for mol in solvent_molecules - ] - - # Extract solvation shells - shells = [ - set( - analyze.evaluate_asl( - st, f"fillres within {radius} mol {mol_num}" + if not skip_solvent_centered_shells: + # Now repeat for solvents to capture solvent-solvent interactions + for species, residue in solvents.items(): + logging.info(f"Extracting shells around {species}") + for radius in solvent_radii: + logging.info(f"Radius = {radius} A") + filtered_shells = [] + for i, st in tqdm(enumerate(structures)): # loop over timesteps + # assign partial charges to atoms + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + + if i > 10: # TODO: fix this + break + + # extract all solvent molecules + solvent_molecules = [ + res for res in st.residue if res.pdbres.strip() == residue + ] + central_solvent_nums = [ + mol.molecule_number for mol in solvent_molecules + ] + + # Extract solvation shells + shells = [ + set( + analyze.evaluate_asl( + st, f"fillres within {radius} mol {mol_num}" + ) + ) + for mol_num in central_solvent_nums + ] + + # Only keep the shells that have no solute atoms and below a maximum size + filtered_shells.extend( + filter_shells_by_size( + filter_shells_with_solute_atoms( + shells, st, solute_resnames + ), + max_shell_size, ) ) - for mol_num in central_solvent_nums + + # Choose a random subset of shells + assert ( + len(filtered_shells) > 0 + ), "No solute-free shells found for solvent" + # check that every shell is below the max size + for shell in filtered_shells: + assert ( + shell.atom_total <= max_shell_size + ), "Expanded shell too large" + random.shuffle(filtered_shells) + filtered_shells = filtered_shells[:1000] + + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + # TODO: speed this up + grouped_shells = group_with_comparison(filtered_shells, are_conformers) + + # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) + grouped_shells = [ + renumber_molecules_to_match(items) for items in grouped_shells ] - # Only keep the shells that have no solute atoms and below a maximum size - filtered_shells.extend( - filter_shells_by_size( - filter_shells_with_solute_atoms(shells, st, solute_resnames), - max_shell_size, - ) + # Now extract the top N most diverse shells from each group + logging.info( + f"Extracting top {top_n} most diverse shells from each group" ) - - # Choose a random subset of shells - assert len(filtered_shells) > 0, "No solute-free shells found for solvent" - # check that every shell is below the max size - for shell in filtered_shells: - assert shell.atom_total <= max_shell_size, "Expanded shell too large" - random.shuffle(filtered_shells) - filtered_shells = filtered_shells[:1000] - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - # TODO: speed this up - grouped_shells = group_with_comparison(filtered_shells, are_conformers) - - # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - grouped_shells = [ - renumber_molecules_to_match(items) for items in grouped_shells - ] - - # Now extract the top N most diverse shells from each group - logging.info(f"Extracting top {top_n} most diverse shells from each group") - final_shells = [] - # example grouping - set of structures - for shell_group in tqdm(grouped_shells): - filtered = filter_by_rmsd(shell_group, n=top_n) - final_shells.extend(filtered) - - # Save the final shells - logging.info(f"Saving final shells") - save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") - os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): - # TODO: seems like this is saving an extra line at the end of the xyz files - st.write(os.path.join(save_path, f"shell_{i}.xyz")) + final_shells = [] + # example grouping - set of structures + for shell_group in tqdm(grouped_shells): + filtered = filter_by_rmsd(shell_group, n=top_n) + final_shells.extend(filtered) + + # Save the final shells + logging.info(f"Saving final shells") + save_path = os.path.join( + save_dir, system_name, species, f"radius={radius}" + ) + os.makedirs(save_path, exist_ok=True) + for i, st in enumerate(final_shells): + # TODO: seems like this is saving an extra line at the end of the xyz files + st.write(os.path.join(save_path, f"shell_{i}.xyz")) if __name__ == "__main__": logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) - random.seed(10) parser = argparse.ArgumentParser() + parser.add_argument( + "--seed", + type=int, + default=10, + help="Random seed", + ) parser.add_argument( "--input_dir", type=str, @@ -246,6 +264,12 @@ def extract_solvation_shells( help="List of shell radii to extract around solutes", ) + parser.add_argument( + "--skip_solvent_centered_shells", + action="store_true", + help="Skip extracting solvent-centered shells", + ) + parser.add_argument( "--solvent_radii", type=list, @@ -269,11 +293,14 @@ def extract_solvation_shells( args = parser.parse_args() + random.seed(args.seed) + extract_solvation_shells( args.input_dir, args.save_dir, args.system_name, args.solute_radii, + args.skip_solvent_centered_shells, args.solvent_radii, args.max_shell_size, args.top_n, From cb1139ca8270c68ad63ba49d8dc539a79ca27370 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 13:46:46 -0700 Subject: [PATCH 066/117] remove equals from dir name --- electrolytes/solvation_shell_extract.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 614b0b7..84b4acd 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -144,7 +144,7 @@ def extract_solvation_shells( # Save the final shells logging.info(f"Saving final shells") - save_path = os.path.join(save_dir, system_name, species, f"radius={radius}") + save_path = os.path.join(save_dir, system_name, species, f"radius_{radius}") os.makedirs(save_path, exist_ok=True) for i, st in enumerate(final_shells): # TODO: seems like this is saving an extra line at the end of the xyz files @@ -229,7 +229,7 @@ def extract_solvation_shells( # Save the final shells logging.info(f"Saving final shells") save_path = os.path.join( - save_dir, system_name, species, f"radius={radius}" + save_dir, system_name, species, f"radius_{radius}" ) os.makedirs(save_path, exist_ok=True) for i, st in enumerate(final_shells): From f7bd798d288e5effe93d209b534f4fb0ea5fdeec Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 13:53:04 -0700 Subject: [PATCH 067/117] assign partial charges once outside loop --- electrolytes/solvation_shell_extract.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 84b4acd..7ca085a 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -77,6 +77,11 @@ def extract_solvation_shells( # Read a structure structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) + # assign partial charges to atoms + for st in structures: + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge + # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin @@ -86,9 +91,6 @@ def extract_solvation_shells( logging.info(f"Radius = {radius} A") expanded_shells = [] for i, st in tqdm(enumerate(structures)): # loop over timesteps - # assign partial charges to atoms - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge if i > 10: # TODO: fix this break From 68dabb2bcf77c430a65309850d2cbbfad8725d6c Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 13:58:51 -0700 Subject: [PATCH 068/117] partial charge assignment once up front --- electrolytes/solvation_shell_extract.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 7ca085a..ce7c0e4 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -78,13 +78,13 @@ def extract_solvation_shells( structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) # assign partial charges to atoms - for st in structures: + logging.info("Assigning partial charges to atoms") + for st in tqdm(structures): for at, charge in zip(st.atom, partial_charges): at.partial_charge = charge # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin - for species, residue in solutes.items(): logging.info(f"Extracting solvation shells around {species}") for radius in solute_radii: From ca95322ee8fd5e87fe4cf581cc02010719a623d2 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 14:03:18 -0700 Subject: [PATCH 069/117] remove size filtering function --- electrolytes/solvation_shell_extract.py | 16 ++++++++-------- electrolytes/solvation_shell_utils.py | 14 -------------- 2 files changed, 8 insertions(+), 22 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index ce7c0e4..73a7b55 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -17,7 +17,6 @@ renumber_molecules_to_match, filter_by_rmsd, filter_shells_with_solute_atoms, - filter_shells_by_size, ) from utils import validate_metadata_file from schrodinger.comparison import are_conformers @@ -186,14 +185,15 @@ def extract_solvation_shells( ] # Only keep the shells that have no solute atoms and below a maximum size - filtered_shells.extend( - filter_shells_by_size( - filter_shells_with_solute_atoms( - shells, st, solute_resnames - ), - max_shell_size, - ) + solute_free_shells = filter_shells_with_solute_atoms( + shells, st, solute_resnames ) + size_filtered_shells = [ + shell + for shell in solute_free_shells + if shell.atom_total <= max_shell_size + ] + filtered_shells.extend(size_filtered_shells) # Choose a random subset of shells assert ( diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index ba0b69e..ed9e0c1 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -12,20 +12,6 @@ from schrodinger.structure import Structure -def filter_shells_by_size( - shells: List[Structure], max_shell_size: int = 200 -) -> List[Structure]: - """ - Filter out shells that are larger than a certain size. - Args: - shells: List of shell structures - max_shell_size: Maximum size (in atoms) of the shell - Returns: - List of structures that correspond to shells that are smaller than max_size - """ - return [shell for shell in shells if shell.atom_total <= max_shell_size] - - def filter_shells_with_solute_atoms( shells: List[Set[int]], st: Structure, solute_res_names: List[str] ) -> List[Structure]: From eb12dd886ec993b73c653cb42ef09c6527f38e04 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 14:18:50 -0700 Subject: [PATCH 070/117] more explicit version of expand shells function --- electrolytes/solvation_shell_utils.py | 30 +++++++++++++++------------ 1 file changed, 17 insertions(+), 13 deletions(-) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index ed9e0c1..e621389 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -60,10 +60,9 @@ def expand_shell( """ # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell shell_ats.add(central_solute) - solutes_included = set([central_solute]) - while len(shell_ats) < max_shell_size: - old_shell_ats = shell_ats.copy() + + def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): new_solutes = set() for at in shell_ats: # If atom is part of a non-central solute molecule - should expand the shell @@ -72,20 +71,26 @@ def expand_shell( and st.atom[at].getResidue().pdbres.strip() in solute_res_names ): new_solutes.add(st.atom[at].molecule_number) - - if new_solutes: - # add entire residues within solvation shell radius of any extra solute atoms - shell_ats.update( - analyze.evaluate_asl( - st, - f'fillres within {radius} mol {",".join([str(i) for i in new_solutes])}', - ) + return new_solutes + + new_solutes = get_new_solutes(st, shell_ats, solutes_included, solute_res_names) + while new_solutes: + # add entire residues within solvation shell radius of any extra solute atoms + new_shell_ats = shell_ats.union( + analyze.evaluate_asl( + st, + f'fillres within {radius} mol {",".join([str(i) for i in new_solutes])}', ) + ) + if len(new_shell_ats) <= max_shell_size: + shell_ats = new_shell_ats solutes_included.update(new_solutes) + new_solutes = get_new_solutes( + st, shell_ats, solutes_included, solute_res_names + ) else: break - shell_ats = old_shell_ats shell_ats = sorted(shell_ats) final_structure = st.extract(shell_ats, copy_props=True) @@ -94,7 +99,6 @@ def expand_shell( # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) - clusterstruct.contract_structure2( final_structure, contract_on_atoms=[central_solute_idx] ) From f4327655f70f2e5d984a8c37c309c403b57c2b73 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 14:47:38 -0700 Subject: [PATCH 071/117] fix central solute molecule bug --- electrolytes/solvation_shell_extract.py | 8 ++++---- electrolytes/solvation_shell_utils.py | 12 +++++++----- 2 files changed, 11 insertions(+), 9 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 73a7b55..96cb2c4 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -77,10 +77,10 @@ def extract_solvation_shells( structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) # assign partial charges to atoms - logging.info("Assigning partial charges to atoms") - for st in tqdm(structures): - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge + # logging.info("Assigning partial charges to atoms") + # for st in tqdm(structures): + # for at, charge in zip(st.atom, partial_charges): + # at.partial_charge = charge # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index e621389..18a385e 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -58,8 +58,8 @@ def expand_shell( Returns: Structure object containing the expanded solvation shell """ - # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell - shell_ats.add(central_solute) + # # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell + # shell_ats.add(st.molecule[central_solute].getAtomList()) solutes_included = set([central_solute]) def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): @@ -94,13 +94,15 @@ def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): shell_ats = sorted(shell_ats) final_structure = st.extract(shell_ats, copy_props=True) - # find index of central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_idx = shell_ats.index(central_solute) + 1 + # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) + central_solute_atom_idx = ( + shell_ats.index(st.molecule[central_solute].getAtomList()[0]) + 1 + ) # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) clusterstruct.contract_structure2( - final_structure, contract_on_atoms=[central_solute_idx] + final_structure, contract_on_atoms=[central_solute_atom_idx] ) return final_structure From 53b61014b6be825d2cbbcebdf14139c11b55d94c Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Tue, 2 Jul 2024 14:55:18 -0700 Subject: [PATCH 072/117] simplify filter solute function --- electrolytes/solvation_shell_extract.py | 8 ++++---- electrolytes/solvation_shell_utils.py | 11 ++++------- 2 files changed, 8 insertions(+), 11 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 96cb2c4..73a7b55 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -77,10 +77,10 @@ def extract_solvation_shells( structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) # assign partial charges to atoms - # logging.info("Assigning partial charges to atoms") - # for st in tqdm(structures): - # for at, charge in zip(st.atom, partial_charges): - # at.partial_charge = charge + logging.info("Assigning partial charges to atoms") + for st in tqdm(structures): + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 18a385e..cdb2cd5 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -24,15 +24,12 @@ def filter_shells_with_solute_atoms( Returns: List of Schrodinger structures that do not contain solute atoms """ - actual_shells = [st.extract(shell, copy_props=True) for shell in shells] + + solute_atoms = analyze.evaluate_asl(st, f'res {",".join(solute_res_names)}') filtered_shells = [ - shell - for shell in actual_shells - if not any( - at.getResidue().pdbres.strip() in solute_res_names for at in shell.atom - ) + shell for shell in shells if not shell.intersection(solute_atoms) ] - return filtered_shells + return [st.extract(shell, copy_props=True) for shell in filtered_shells] def expand_shell( From 1af70a4af3505ad9f5fd426fbc3e6b3e5dbeb07b Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 3 Jul 2024 21:23:10 +0000 Subject: [PATCH 073/117] filter after batches are made --- metal-organics/mprun.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/metal-organics/mprun.py b/metal-organics/mprun.py index 5a9b484..5f1ca4f 100644 --- a/metal-organics/mprun.py +++ b/metal-organics/mprun.py @@ -100,8 +100,6 @@ def main(): # Add index as name of job from input dataframe. newindf_rows = [] for i, row in indf.iterrows(): - if str(i) in done_list: - continue inp_dict = row["architector_input"] inp_dict["name"] = str(i) newindf_rows.append(inp_dict) @@ -111,6 +109,7 @@ def main(): batch = newindf_rows[ batch_idx * args.batch_size : (batch_idx + 1) * args.batch_size ] + batch = [inp for inp in batch if inp['name'] not in done_list] list(tqdm(pool.imap(fxn, batch), total=len(batch))) From 4d9f53b4e0d1ece130d5eabb9b39e4c3f188733f Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 3 Jul 2024 21:23:56 +0000 Subject: [PATCH 074/117] label ligands after coordinating groups --- biomolecules/pdb_pockets/biolip_extraction.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 5ef7e45..78b4f48 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -196,7 +196,6 @@ def retreive_ligand_and_env( # random.seed(12341) grouped_biolip = biolip_df.groupby("pdb_id") pdb_list = list(grouped_biolip.groups.keys()) - pdb_list = ['1a0q'] for pdb_count in range(start_pdb, end_pdb): # pdb_id = random.choice(list(grouped_biolip.groups.keys())) pdb_id = pdb_list[pdb_count] @@ -550,12 +549,12 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats ] - # mark the ligand chain - for at in lig_ats: - st.atom[at].chain = "l" # mark the coord chain for at in coord_ats: st.atom[at].chain = "c" + # mark the ligand chain + for at in lig_ats: + st.atom[at].chain = "l" # mark the receptor chain for at in res_ats: st.atom[at].chain = "A" From aa7d0244142c05b705c5d524647977c495e8fa82 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Thu, 4 Jul 2024 09:40:53 -0700 Subject: [PATCH 075/117] turn off shell expansion if there are no solvents --- .gitignore | 1 + electrolytes/run_extraction.sh | 2 +- electrolytes/solvation_shell_extract.py | 50 ++++++++++++++++++------- electrolytes/solvation_shell_utils.py | 21 ++--------- 4 files changed, 41 insertions(+), 33 deletions(-) diff --git a/.gitignore b/.gitignore index 61755b7..0eea8d6 100644 --- a/.gitignore +++ b/.gitignore @@ -127,5 +127,6 @@ maestro_package/ # Misc notes.txt +*prof diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index fd2e72d..28cb49d 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -2,7 +2,7 @@ #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? -$SCHRODINGER/run python3 solvation_shell_extract.py --input_dir 'testfiles/1' \ +$SCHRODINGER/run python3 -m cProfile -o output100.prof solvation_shell_extract.py --input_dir 'testfiles/1' \ --save_dir 'results' \ --system_name 'Li_BF4' \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 73a7b55..5492edd 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -21,6 +21,7 @@ from utils import validate_metadata_file from schrodinger.comparison import are_conformers from schrodinger.application.jaguar.utils import group_with_comparison +from schrodinger.application.matsci import clusterstruct from schrodinger.structutils import rmsd @@ -77,10 +78,11 @@ def extract_solvation_shells( structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) # assign partial charges to atoms - logging.info("Assigning partial charges to atoms") - for st in tqdm(structures): - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge + # TODO: fix this - the iterator over structures can only be called once + # logging.info("Assigning partial charges to atoms") + # for st in tqdm(structures): + # for at, charge in zip(st.atom, partial_charges): + # at.partial_charge = charge # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin @@ -91,7 +93,7 @@ def extract_solvation_shells( expanded_shells = [] for i, st in tqdm(enumerate(structures)): # loop over timesteps - if i > 10: # TODO: fix this + if i > 100: # TODO: fix this break # extract all solute molecules @@ -110,14 +112,34 @@ def extract_solvation_shells( ] # Now expand the shells - for shell, central_solute in zip(shells, central_solute_nums): - expanded_shell = expand_shell( - st, - shell, - central_solute, - radius, - solute_resnames, - max_shell_size=max_shell_size, + for shell_ats, central_solute in zip(shells, central_solute_nums): + expanded_shell_ats = shell_ats + # If we have a solvent-free system, don't expand shells around solutes, + # because we'll always have solutes and will never terminate + if solvent_resnames: + expanded_shell_ats = expand_shell( + st, + shell_ats, + central_solute, + radius, + solute_resnames, + max_shell_size=max_shell_size, + ) + expanded_shell_ats = sorted(expanded_shell_ats) + expanded_shell = st.extract(expanded_shell_ats, copy_props=True) + + # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) + central_solute_atom_idx = ( + expanded_shell_ats.index( + st.molecule[central_solute].getAtomList()[0] + ) + + 1 + ) + + # contract everthing to be centered on our molecule of interest + # (this will also handle if a molecule is split across a PBC) + clusterstruct.contract_structure2( + expanded_shell, contract_on_atoms=[central_solute_atom_idx] ) assert ( expanded_shell.atom_total <= max_shell_size @@ -163,7 +185,7 @@ def extract_solvation_shells( for at, charge in zip(st.atom, partial_charges): at.partial_charge = charge - if i > 10: # TODO: fix this + if i > 100: # TODO: fix this break # extract all solvent molecules diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index cdb2cd5..c2f16bd 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -39,7 +39,7 @@ def expand_shell( radius: float, solute_res_names: List[str], max_shell_size: int = 200, -) -> Structure: +) -> Set[int]: """ Expands a solvation shell. If there are any (non-central) solutes present in the shell, recursively include shells around those solutes. @@ -53,10 +53,8 @@ def expand_shell( solute_res_names: List of residue names that correspond to solute atoms in the simulation max_shell_size: Maximum size (in atoms) of the expanded shell Returns: - Structure object containing the expanded solvation shell + Set of atom indices (of `st`) of the expanded shell (1-indexed) """ - # # TODO: I'm not sure why we have to do this, but sometimes the central solute is not in the shell - # shell_ats.add(st.molecule[central_solute].getAtomList()) solutes_included = set([central_solute]) def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): @@ -88,20 +86,7 @@ def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): else: break - shell_ats = sorted(shell_ats) - final_structure = st.extract(shell_ats, copy_props=True) - - # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_atom_idx = ( - shell_ats.index(st.molecule[central_solute].getAtomList()[0]) + 1 - ) - - # contract everthing to be centered on our molecule of interest - # (this will also handle if a molecule is split across a PBC) - clusterstruct.contract_structure2( - final_structure, contract_on_atoms=[central_solute_atom_idx] - ) - return final_structure + return shell_ats def filter_by_rmsd(shells: List[Structure], n: int = 20) -> List[Structure]: From 34d2f2187a2824c8680f3c0705383df41dde475c Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Thu, 4 Jul 2024 10:19:05 -0700 Subject: [PATCH 076/117] lognormal sampling of max size --- electrolytes/solvation_shell_extract.py | 9 ++++++++- electrolytes/solvation_shell_utils.py | 16 ++++++++++++++++ 2 files changed, 24 insertions(+), 1 deletion(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 5492edd..bfdf7a8 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -17,6 +17,7 @@ renumber_molecules_to_match, filter_by_rmsd, filter_shells_with_solute_atoms, + generate_lognormal_samples, ) from utils import validate_metadata_file from schrodinger.comparison import are_conformers @@ -117,13 +118,19 @@ def extract_solvation_shells( # If we have a solvent-free system, don't expand shells around solutes, # because we'll always have solutes and will never terminate if solvent_resnames: + # TODO: how to choose the mean/scale for sampling? + # Should the mean be set to the number of atoms in the non-expanded shell? + upper_bound = max( + len(shell_ats), generate_lognormal_samples()[0] + ) + upper_bound = min(upper_bound, max_shell_size) expanded_shell_ats = expand_shell( st, shell_ats, central_solute, radius, solute_resnames, - max_shell_size=max_shell_size, + max_shell_size=upper_bound, ) expanded_shell_ats = sorted(expanded_shell_ats) expanded_shell = st.extract(expanded_shell_ats, copy_props=True) diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index c2f16bd..6b19441 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -12,6 +12,22 @@ from schrodinger.structure import Structure +def generate_lognormal_samples(loc=75, sigma=0.45, size=1): + """ + Generate random samples from a lognormal distribution. + + Parameters: + - loc: float, mean of the distribution + - sigma: float, standard deviation of the log of the distribution + - size: int, number of samples to generate (default is 1000) + + Returns: + - samples: numpy array, random samples from the lognormal distribution + """ + samples = np.random.lognormal(mean=np.log(loc), sigma=sigma, size=size) + return samples + + def filter_shells_with_solute_atoms( shells: List[Set[int]], st: Structure, solute_res_names: List[str] ) -> List[Structure]: From a51ea9be470dc28110b48be27f4aad5a29cb74ce Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Thu, 4 Jul 2024 10:58:09 -0700 Subject: [PATCH 077/117] option to subsample solutes/solvents per frame --- electrolytes/solvation_shell_extract.py | 34 ++++++++++++++++++------- 1 file changed, 25 insertions(+), 9 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index bfdf7a8..17ae4b4 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -33,6 +33,7 @@ def extract_solvation_shells( solute_radii: List[float], skip_solvent_centered_shells: bool, solvent_radii: List[float], + shells_per_frame: int, max_shell_size: int, top_n: int, ): @@ -47,6 +48,7 @@ def extract_solvation_shells( solute_radii: List of shell radii to extract around solutes. skip_solvent_centered_shells: Skip extracting solvent-centered shells. solvent_radii: List of shell radii to extract around solvents. + shells_per_frame: Number of solutes or solvents per MD simulation frame from which to extract candidate shells. max_shell_size: Maximum size (in atoms) of saved shells. top_n: Number of snapshots to extract per topology. """ @@ -94,13 +96,15 @@ def extract_solvation_shells( expanded_shells = [] for i, st in tqdm(enumerate(structures)): # loop over timesteps - if i > 100: # TODO: fix this - break - # extract all solute molecules solute_molecules = [ res for res in st.residue if res.pdbres.strip() == residue ] + + # Subsample a random set of k solute molecules + if shells_per_frame > 0: + solute_molecules = random.sample(solute_molecules, shells_per_frame) + central_solute_nums = [mol.molecule_number for mol in solute_molecules] # Extract solvation shells shells = [ @@ -168,17 +172,18 @@ def extract_solvation_shells( logging.info(f"Extracting top {top_n} most diverse shells from each group") final_shells = [] # example grouping - set of structures - for shell_group in tqdm(grouped_shells): + for group_idx, shell_group in tqdm(enumerate(grouped_shells)): filtered = filter_by_rmsd(shell_group, n=top_n) + filtered = [(group_idx, st) for st in filtered] final_shells.extend(filtered) # Save the final shells logging.info(f"Saving final shells") save_path = os.path.join(save_dir, system_name, species, f"radius_{radius}") os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): + for i, (group_idx, st) in enumerate(final_shells): # TODO: seems like this is saving an extra line at the end of the xyz files - st.write(os.path.join(save_path, f"shell_{i}.xyz")) + st.write(os.path.join(save_path, f"group_{group_idx}" f"shell_{i}.xyz")) if not skip_solvent_centered_shells: # Now repeat for solvents to capture solvent-solvent interactions @@ -192,13 +197,16 @@ def extract_solvation_shells( for at, charge in zip(st.atom, partial_charges): at.partial_charge = charge - if i > 100: # TODO: fix this - break - # extract all solvent molecules solvent_molecules = [ res for res in st.residue if res.pdbres.strip() == residue ] + + # Subsample a random set of k solvent molecules + if shells_per_frame > 0: + solvent_molecules = random.sample( + solvent_molecules, shells_per_frame + ) central_solvent_nums = [ mol.molecule_number for mol in solvent_molecules ] @@ -308,6 +316,13 @@ def extract_solvation_shells( help="List of shell radii to extract around solvents", ) + parser.add_argument( + "--shells_per_frame", + type=int, + default=-1, + help="Number of solutes or solvents per MD simulation frame from which to extract candidate shells", + ) + parser.add_argument( "--max_shell_size", type=int, @@ -333,6 +348,7 @@ def extract_solvation_shells( args.solute_radii, args.skip_solvent_centered_shells, args.solvent_radii, + args.shells_per_frame, args.max_shell_size, args.top_n, ) From 23e320a181f383f0ecb87831db3ea192bc7eca0c Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:18:16 +0000 Subject: [PATCH 078/117] fix chain-labeling/angle adjustment bug --- biomolecules/pdb_pockets/biolip_extraction.py | 89 ++++++------------- 1 file changed, 29 insertions(+), 60 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 78b4f48..0d517be 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -205,7 +205,7 @@ def retreive_ligand_and_env( for idx, row in rows.iterrows(): sys.stdout.flush() binding_site_counter = ( - row["binding_site_number_code"] + row["receptor_chain"] + row["receptor_chain"] + row["binding_site_number_code"] ) try: st, fname = get_prepped_protein(pdb_id, row, fill_sidechain) @@ -271,7 +271,7 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id: str, chains: List[str]) -> Tuple[str, str]: +def download_cif(pdb_id: str, chains: List[str]) -> str: """ Download cif (as opposed to pdb) of a given protein and extract the needed chains. @@ -292,39 +292,7 @@ def download_cif(pdb_id: str, chains: List[str]) -> Tuple[str, str]: else: raise ConnectionError - st = StructureReader.read(cif_name) - # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours - at_list = [] - for chain in chains: - at_list.extend(st.chain[chain].getAtomList()) - st = st.extract(at_list) - fname = f"{pdb_id}.maegz" - outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" - with StructureWriter(fname) as writer: - writer.append(st) - return fname, outname - - -def missing_backbone_check(st: Structure): - """ - Check if the protein backbone is present in the structure - - Rarely, some protein structures are just C alpha positions. We check - for this by making sure that the structure doesn't contain lots of - isolated carbon atoms. - - :param st: structure to check - :raises: OnlyCAError if structure seems like it is only CA - """ - if ( - sum( - 1 - for mol in st.molecule - if len(mol.atom) == 1 and mol.atom[1].element == "C" - ) - > 20 - ): - raise OnlyCAError + return cif_name def get_prepped_protein( @@ -346,17 +314,10 @@ def get_prepped_protein( download a PDB as is :return: Prepared structure and its filename for subsequent clean-up """ - baseoutname = f"{pdb_id}_prepped.maegz" - pdb_name = pdb_id chains = {row["receptor_chain"], row["ligand_chain"]} - if len(chains) == 1: - solo_chain = next(iter(chains)) - pdb_name += f":{solo_chain}" - outname = f"{pdb_id}_{solo_chain}_prepped.maegz" - else: - outname = baseoutname - basename = pdb_name.replace(":", "_") - fname = basename + ".pdb" + outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" + fname = f"{pdb_id}.pdb" + maename = f"{pdb_id}.maegz" if not prep: subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) @@ -364,26 +325,26 @@ def get_prepped_protein( elif os.path.exists(outname): # We've already done this example pass - elif os.path.exists(baseoutname): - # We've not done this chain, but we have done the whole protein - outname = baseoutname else: # We haven't done anything to prepare the protein - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_name]) + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) if not os.path.exists(fname): # PDB could not be downloaded, try the cif - fname, outname = download_cif(pdb_id, chains) + fname = download_cif(pdb_id, chains) st = next(StructureReader(fname), None) if st is None: raise ValueError - # Reject structure that are just a bunch of CA - # missing_backbone_check(st) + # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours + at_list = [] + for chain in chains: + at_list.extend(st.chain[chain].getAtomList()) + st = st.extract(at_list) # Remove any dummy atoms, PrepWizard doesn't like them dummy_atoms = [at for at in st.atom if at.atomic_number < 1] st.deleteAtoms(dummy_atoms) - st.write(fname) + st.write(maename) # Run PrepWizard if not os.path.exists(outname): @@ -391,7 +352,7 @@ def get_prepped_protein( # for PDBs that have to be downloaded as CIFs isn't known until after # we download them and can see their chain names. try: - run_prepwizard(fname, outname, fill_sidechain) + run_prepwizard(maename, outname, fill_sidechain) except subprocess.TimeoutExpired: raise RuntimeError("PrepWizard took longer than 2 hours, skipping") if not os.path.exists(outname): @@ -399,14 +360,17 @@ def get_prepped_protein( st = StructureReader.read(outname) st = build.remove_alternate_positions(st) - deprotonate_phosphate_esters(st) + if deprotonate_phosphate_esters(st): + print( + f'{pdb_id}, {row["receptor_chain"]}{row["binding_site_number_code"]} needed phosphate deprotonation' + ) st = build.reorder_protein_atoms_by_sequence(st) # Cleanup - for file_to_del in (fname, f"{pdb_id}.pdb", f"{pdb_id}.cif"): + for file_to_del in (maename, fname): if os.path.exists(file_to_del): os.remove(file_to_del) - for deldir in glob.glob(f"{basename}-???"): + for deldir in glob.glob(f"{maename.remove('.mae')}-???"): shutil.rmtree(deldir) sys.stdout.flush() return st, outname @@ -452,15 +416,16 @@ def run_prepwizard(fname: str, outname: str, fill_sidechain: bool) -> None: ) -def deprotonate_phosphate_esters(st: Structure) -> None: +def deprotonate_phosphate_esters(st: Structure) -> bool: """ At physiological pH, it's a good assumption that any phosphate esters will be deprotonated. In the absence pKa's for ligands, we will make this assumption. :param st: Structure with phosphate groups that can be deprotonated + :return: True if structure needed to be deprotonated """ - phos_smarts = "[*;!#1][*][P](=[O])([O])([O][H])" + phos_smarts = "[*;!#1][*][P](=[O,S])([O])([O][H])" try: matched_ats = evaluate_smarts(st, phos_smarts) except ValueError: @@ -470,6 +435,7 @@ def deprotonate_phosphate_esters(st: Structure) -> None: for O_at in O_ats: st.atom[O_at].formal_charge -= 1 st.deleteAtoms(H_ats) + return bool(H_ats) def make_gaps_gly(st: Structure, row: pd.Series, gap_res: List[str]) -> None: @@ -549,6 +515,9 @@ def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]] at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats ] + # mark the protein as unused, we will edit the parts we want + for ch in st.chain: + ch.name = "X" # mark the coord chain for at in coord_ats: st.atom[at].chain = "c" @@ -604,7 +573,7 @@ def cap_termini(st: Structure, ligand_env: Structure) -> None: :param st: original protein structure from which the pocket was extracted :param ligand_env: extracted protein receptor (i.e. ligand environment) """ - capterm = CapTermini(ligand_env, verbose=False, frag_min_atoms=0) + capterm = CapTermini(ligand_env, verbose=False, frag_min_atoms=3) for res in capterm.cappedResidues(): orig_res = st.findResidue(res) new_res = ligand_env.findResidue(res) From c0f36e8c00f010c117fda438f77e770ad43306ca Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:27:38 +0000 Subject: [PATCH 079/117] add cleanup script for pdb pockets --- biomolecules/pdb_pockets/cleanup.py | 108 ++++++++++++++++++++++++++++ 1 file changed, 108 insertions(+) create mode 100644 biomolecules/pdb_pockets/cleanup.py diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py new file mode 100644 index 0000000..1ba7a67 --- /dev/null +++ b/biomolecules/pdb_pockets/cleanup.py @@ -0,0 +1,108 @@ + +""" + Cap cleaved cysteines with H + Find ACE in ligand chain and remove ACE but first find the adjacent N + at=next((at for at in res.getCarbonylCarbon().bonded_atoms if at.element == 'N')) + verify that this N has 4 bonds and if so delete the ACE, increase charge to 1 and + call build.add_hydrogens(st, atom_list=[at]) on it + What to do with NME? +""" +import argparse +import glob +import os +from tqdm import tqdm +from schrodinger.structure import StructureReader, StructureWriter, Structure +from schrodinger.structutils import analyze, build + +def rename_coord_chain(st): + chain_names = [ch.name for ch in st.chain] + if 'l' not in chain_names and 'c' in chain_names: + lig = [] + if len(st.chain['c'].getAtomList()) == 1: + lig = st.chain['c'].getAtomList() + if not lig: + lig = analyze.evaluate_asl(st, 'chain c and metals') + if not lig: + lig = analyze.evaluate_asl(st, 'chain c and res D8U') + if not lig: + lig = analyze.evaluate_asl(st, 'chain c and atom.ato >=18') + if not lig: + lig = analyze.evaluate_asl(st, 'chain c and atom.ele F,Cl,Br,I') + for at in lig: + st.atom[at].chain = 'l' + if lig: + return True + return False + +def fix_disrupted_disulfides(st): + broken_cysteines = analyze.evaluate_asl(st, 'atom.pt SG and atom.att 1') + if broken_cysteines: + build.add_hydrogens(st, atom_list=broken_cysteines) + return True + return False + +def remove_ligand_ace_cap(st): + ats_to_delete = [] + N_to_protonate = [] + for res in st.chain['l'].residue: + if res.pdbres.strip() == 'ACE' and len(st.chain['l'].getAtomList()) != 6: + capped_N = next((at for at in res.getCarbonylCarbon().bonded_atoms if at.element == 'N')) + ats_to_delete.extend(res.getAtomList()) + N_to_protonate.append(capped_N) + for at in N_to_protonate: + st.atom[at].formal_charge += 1 + if N_to_protonate: + st.deleteAtoms(ats_to_delete) + build.add_hydrogens(st, atom_list = N_to_protonate) + return True + return False + +def remove_ligand_nma_cap(st): + ats_to_delete = [] + for res in st.chain['l'].residue: + if res.pdbres.strip() == 'NMA' and len(res.getAtomList()) == 6: + n_at = res.getBackboneNitrogen() + if n_at is None: + raise RuntimeError + ats_to_delete.extend(res.getAtomList()) + ats_to_delete.remove(n_at.index) + n_at.element = 'O' + n_at.formal_charge = -1 + for b_at in n_at.bonded_atoms: + adj_res = b_at.getResidue() + if adj_res != res: + break + n_at.resnum = adj_res.resnum + n_at.inscode = adj_res.inscode + n_at.pdbres = adj_res.pdbres + n_at.pdbname = '' + st.deleteAtoms(ats_to_delete) + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument("--output_path", default=".") + parser.add_argument("--prefix", default='') + return parser.parse_args() + +def main(): + args = parse_args() + for fname in tqdm(glob.glob(os.path.join(args.output_path, f'{args.prefix}*.pdb'))): + st = StructureReader.read(fname) + change_made = rename_coord_chain(st) + change_made = fix_disrupted_disulfides(st) or change_made + try: + change_made = remove_ligand_ace_cap(st) or change_made + except: + print(fname) + raise + try: + change_made = remove_ligand_nma_cap(st) or change_made + except: + print(fname) + raise + if change_made: + st = build.reorder_protein_atoms_by_sequence(st) + st.write(fname) + +if __name__ == "__main__": + main() From b487187e260f102fb64ce5eab2d7f93cf83feadf Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:40:03 +0000 Subject: [PATCH 080/117] cleanup cleanup.py --- biomolecules/pdb_pockets/cleanup.py | 94 +++++++++++++++-------------- 1 file changed, 49 insertions(+), 45 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 1ba7a67..b506c7a 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -1,72 +1,73 @@ - -""" - Cap cleaved cysteines with H - Find ACE in ligand chain and remove ACE but first find the adjacent N - at=next((at for at in res.getCarbonylCarbon().bonded_atoms if at.element == 'N')) - verify that this N has 4 bonds and if so delete the ACE, increase charge to 1 and - call build.add_hydrogens(st, atom_list=[at]) on it - What to do with NME? -""" import argparse import glob import os -from tqdm import tqdm -from schrodinger.structure import StructureReader, StructureWriter, Structure + +from schrodinger.structure import Structure, StructureReader, StructureWriter from schrodinger.structutils import analyze, build +from tqdm import tqdm -def rename_coord_chain(st): - chain_names = [ch.name for ch in st.chain] - if 'l' not in chain_names and 'c' in chain_names: - lig = [] - if len(st.chain['c'].getAtomList()) == 1: - lig = st.chain['c'].getAtomList() - if not lig: - lig = analyze.evaluate_asl(st, 'chain c and metals') - if not lig: - lig = analyze.evaluate_asl(st, 'chain c and res D8U') - if not lig: - lig = analyze.evaluate_asl(st, 'chain c and atom.ato >=18') - if not lig: - lig = analyze.evaluate_asl(st, 'chain c and atom.ele F,Cl,Br,I') - for at in lig: - st.atom[at].chain = 'l' - if lig: - return True - return False -def fix_disrupted_disulfides(st): - broken_cysteines = analyze.evaluate_asl(st, 'atom.pt SG and atom.att 1') +def fix_disrupted_disulfides(st: Structure) -> bool: + """ + If a cysteine sulfur is missing a hydrogen, add it. + + This occurs when a cysteine residue which is part of a disulfide + bond is extracted but its corresponding partner is not, leaving + a "bare" S. + + :param st: Structure to correct + :return: If a change was made, return True + """ + broken_cysteines = analyze.evaluate_asl(st, "atom.pt SG and atom.att 1") if broken_cysteines: build.add_hydrogens(st, atom_list=broken_cysteines) return True return False -def remove_ligand_ace_cap(st): + +def remove_ligand_ace_cap(st: Structure) -> bool: + """ + If there is an ACE added to a ligand (and the ACE is not itself the ligand), + remove it and recover what is likely a protonated N. + + :param st: Structure to correct + :return: If a change was made, return True + """ ats_to_delete = [] N_to_protonate = [] - for res in st.chain['l'].residue: - if res.pdbres.strip() == 'ACE' and len(st.chain['l'].getAtomList()) != 6: - capped_N = next((at for at in res.getCarbonylCarbon().bonded_atoms if at.element == 'N')) + for res in st.chain["l"].residue: + if res.pdbres.strip() == "ACE" and len(st.chain["l"].getAtomList()) != 6: + capped_N = next( + (at for at in res.getCarbonylCarbon().bonded_atoms if at.element == "N") + ) ats_to_delete.extend(res.getAtomList()) N_to_protonate.append(capped_N) for at in N_to_protonate: st.atom[at].formal_charge += 1 if N_to_protonate: st.deleteAtoms(ats_to_delete) - build.add_hydrogens(st, atom_list = N_to_protonate) + build.add_hydrogens(st, atom_list=N_to_protonate) return True return False -def remove_ligand_nma_cap(st): + +def remove_ligand_nma_cap(st: Structure) -> bool: + """ + If there is an NMA added to a ligand (and the ligand is not NMA), + remove it and recover what is likely a deprotonated O. + + :param st: Structure to correct + :return: If a change was made, return True + """ ats_to_delete = [] - for res in st.chain['l'].residue: - if res.pdbres.strip() == 'NMA' and len(res.getAtomList()) == 6: + for res in st.chain["l"].residue: + if res.pdbres.strip() == "NMA" and len(res.getAtomList()) == 6: n_at = res.getBackboneNitrogen() if n_at is None: raise RuntimeError ats_to_delete.extend(res.getAtomList()) ats_to_delete.remove(n_at.index) - n_at.element = 'O' + n_at.element = "O" n_at.formal_charge = -1 for b_at in n_at.bonded_atoms: adj_res = b_at.getResidue() @@ -75,20 +76,22 @@ def remove_ligand_nma_cap(st): n_at.resnum = adj_res.resnum n_at.inscode = adj_res.inscode n_at.pdbres = adj_res.pdbres - n_at.pdbname = '' + n_at.pdbname = "" st.deleteAtoms(ats_to_delete) + return bool(ats_to_delete) + def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--output_path", default=".") - parser.add_argument("--prefix", default='') + parser.add_argument("--prefix", default="") return parser.parse_args() + def main(): args = parse_args() - for fname in tqdm(glob.glob(os.path.join(args.output_path, f'{args.prefix}*.pdb'))): + for fname in tqdm(glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb"))): st = StructureReader.read(fname) - change_made = rename_coord_chain(st) change_made = fix_disrupted_disulfides(st) or change_made try: change_made = remove_ligand_ace_cap(st) or change_made @@ -104,5 +107,6 @@ def main(): st = build.reorder_protein_atoms_by_sequence(st) st.write(fname) + if __name__ == "__main__": main() From b24eac1dfa7682b759bda4b55c18bfdcf3d8266a Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:57:00 +0000 Subject: [PATCH 081/117] add combine_pockets.py to merge certain pockets --- biomolecules/pdb_pockets/combine_pockets.py | 169 ++++++++++++++++++++ 1 file changed, 169 insertions(+) create mode 100644 biomolecules/pdb_pockets/combine_pockets.py diff --git a/biomolecules/pdb_pockets/combine_pockets.py b/biomolecules/pdb_pockets/combine_pockets.py new file mode 100644 index 0000000..2acac3f --- /dev/null +++ b/biomolecules/pdb_pockets/combine_pockets.py @@ -0,0 +1,169 @@ +import argparse +import glob +import os +from typing import Optional + +import pandas as pd +from schrodinger.structure import Structure, StructureReader +from schrodinger.structutils import measure +from tqdm import tqdm + +from biolip_extraction import get_biolip_db + + +def combine_pockets(biolip_df: pd.DataFrame, path: str): + """ + Combine entries that correspond to the same pocket. + + If a ligand is interacting with multiple receptor chains, they will + appear as different entries in BioLiP and therefore different structures + here. We should combine such structures into one structure. + + :param biolip_df: DataFrame storing BioLiP database + :param path: Path to extracted pockets + """ + shared_pockets = biolip_df[ + biolip_df.duplicated( + subset=["pdb_id", "ligand_id", "ligand_chain", "ligand_residue_number"], + keep=False, + ) + ] + grouped_pockets = shared_pockets.groupby( + ["pdb_id", "ligand_id", "ligand_chain", "ligand_residue_number"], + group_keys=False, + ) + file_list = glob.glob(os.path.join(path, "*.pdb")) + for key, item in tqdm(grouped_pockets): + old_names = [] + combined_st = None + out_name = key[0] + count = 0 + for idx, row in item.iterrows(): + bs_name = f'{row["receptor_chain"]}{row["binding_site_number_code"]}' + start = os.path.join(path, f'{row["pdb_id"]}_{bs_name}_') + fname = [ + f + for f in file_list + if f.startswith(start) and len(os.path.basename(f).split("_")) == 3 + ] + if not fname: + continue + assert len(fname) == 1 + fname = fname.pop() + st = StructureReader.read(fname) + try: + combined_st = merge_structures(combined_st, st, count) + except KeyError: + print(fname) + print(old_names) + raise + count += 1 + old_names.append(fname) + out_name += f"_{bs_name}" + if combined_st is not None: + out_name += f"_{combined_st.formal_charge}" + # for fname in old_names: + # os.remove(fname) + combined_st.write(os.path.join(path, out_name + ".pdb")) + + +def get_ligand_chain_bonds(st: Structure) -> dict[int:tuple]: + """ + Get bonds between ligand and receptor chains + + We will need to copy these bonds into the combined structure, as we + have only one copy of the ligand and potentially multiple attachment + sites. + + :param st: Structure to get bonds in + :return: Dictionary relating the index of the ligand atom to a tuple + of the StructureAtom object (so that new numbering can be + extracted when atoms are deleted) and bond order (which would + disappear if one of the atoms were deleted) + """ + comb_cov = {} + for bond in st.bond: + chains = {at.chain for at in bond.atom} + if "l" in chains and any(ch.isupper() for ch in chains): + if bond.atom1.chain == "l": + comb_cov[bond.atom1.index] = (bond.atom2, bond.order) + else: + comb_cov[bond.atom2.index] = (bond.atom1, bond.order) + return comb_cov + + +def merge_structures( + combined_st: Optional[Structure], st: Structure, count: int +) -> Structure: + """ + Merge the structures + + This requires: + 1) Determining what ligand-receptor bonds are present in `st` + 2) Deleting duplicated atoms (i.e. the ligand and any coordinating atoms) from `st` + 3) Combining `combined_st` and `st` + 4) Recovering ligand-receptor bonds which may have been deleted in Step 2 + 5) If the newly added chain had previously been picked up as + coordinating atoms, remove those coordinating atoms in favor + of the equivalent receptor atoms + + :param combined_st: Structure (or None if we are just starting) to + collect combined structure into + :param st: Structure to add to combined_st + :param count: How many structures have been added (this is to keep track of chain names) + :return: Newly combined structure + """ + if combined_st is None: + return st + # Get covalent bonds between ligands and receptor chains + new_cov = get_ligand_chain_bonds(st) + + # Figure out the equivalent atom numbers between + comb_copy = combined_st.copy() + comb_copy.extend(st) + offset = combined_st.atom_total + remapped_cov = {} + for pair in measure.get_close_atoms(comb_copy, dist=0.01): + if max(pair) - offset in new_cov: + remapped_cov[min(pair)] = new_cov[max(pair) - offset] + + # delete ligand atoms + ligand_ats = st.chain["l"].getAtomList() + if "c" in (ch.name for ch in st.chain): + ligand_ats.extend(st.chain["c"].getAtomList()) + st.deleteAtoms(ligand_ats) + for at in st.atom: + at.chain = chr(65 + count) + + # combine structures and recover ligand-receptor bonds + combined_st.extend(st) + for lig_at, (chain_at, order) in remapped_cov.items(): + if not combined_st.areBound(lig_at, chain_at.index + offset): + combined_st.addBond(lig_at, chain_at.index + offset, order) + + # Resolve any coordinating atoms in favor of a receptor atom + close_atoms = measure.get_close_atoms(combined_st, dist=0.01) + ats_to_delete = [] + for at1, at2 in close_atoms: + if combined_st.atom[at2].chain == "c": + ats_to_delete.append(at2) + elif combined_st.atom[at1].chain == "c": + ats_to_delete.append(at1) + combined_st.deleteAtoms(ats_to_delete) + return combined_st + + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument("--output_path", default=".") + return parser.parse_args() + + +def main(): + args = parse_args() + biolip_df = get_biolip_db(pklpath=args.output_path) + combine_pockets(biolip_df, args.output_path) + + +if __name__ == "__main__": + main() From d413430e0a2812c1f2db0c0f391c1cc8995acde8 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:57:56 +0000 Subject: [PATCH 082/117] flake8 --- biomolecules/pdb_pockets/cleanup.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index b506c7a..1d602aa 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -2,7 +2,7 @@ import glob import os -from schrodinger.structure import Structure, StructureReader, StructureWriter +from schrodinger.structure import Structure, StructureReader from schrodinger.structutils import analyze, build from tqdm import tqdm @@ -92,7 +92,7 @@ def main(): args = parse_args() for fname in tqdm(glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb"))): st = StructureReader.read(fname) - change_made = fix_disrupted_disulfides(st) or change_made + change_made = fix_disrupted_disulfides(st) try: change_made = remove_ligand_ace_cap(st) or change_made except: From 39abfb0f44804859002a05f21f0b7b0e2d2f3dae Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 5 Jul 2024 18:59:08 +0000 Subject: [PATCH 083/117] remove correct directory --- biomolecules/pdb_pockets/biolip_extraction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 0d517be..0cc7a54 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -370,7 +370,7 @@ def get_prepped_protein( for file_to_del in (maename, fname): if os.path.exists(file_to_del): os.remove(file_to_del) - for deldir in glob.glob(f"{maename.remove('.mae')}-???"): + for deldir in glob.glob(f"{pdb_id}-???"): shutil.rmtree(deldir) sys.stdout.flush() return st, outname From 66fcc21f43078b99df863a8620801e6175c825a1 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 8 Jul 2024 17:39:08 +0000 Subject: [PATCH 084/117] updates --- biomolecules/pdb_pockets/biolip_extraction.py | 99 +++++++++++-------- 1 file changed, 60 insertions(+), 39 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 0cc7a54..17aa8c8 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -17,10 +17,6 @@ SCHRO = "/private/home/levineds/schrodinger2024-2" -class OnlyCAError(Exception): - pass - - class MissingAtomsError(Exception): pass @@ -169,6 +165,22 @@ def get_minimal_pockets(group: pd.DataFrame) -> List[int]: return group.loc[[row.name for row in subset_rows]] +def certain_rows(df): + rows = [ + ("6qs4", "D", "BS03"), + ] # ('6qs4', 'D', 'BS02')] + rows_df = pd.DataFrame( + rows, columns=["pdb_id", "receptor_chain", "binding_site_number_code"] + ) + filtered = pd.merge( + df, + rows_df, + how="inner", + on=["pdb_id", "receptor_chain", "binding_site_number_code"], + ) + return filtered + + def retreive_ligand_and_env( biolip_df: pd.DataFrame, ligand_size_limit: int = 250, @@ -194,8 +206,13 @@ def retreive_ligand_and_env( :param fill_sidechain: If True, PrepWizard will try and fill in missing side chains """ # random.seed(12341) + # biolip_df = certain_rows(biolip_df) grouped_biolip = biolip_df.groupby("pdb_id") pdb_list = list(grouped_biolip.groups.keys()) + done_list = { + tuple(os.path.basename(f).split("_")[:2]) + for f in glob.glob(output_path + "*.pdb") + } for pdb_count in range(start_pdb, end_pdb): # pdb_id = random.choice(list(grouped_biolip.groups.keys())) pdb_id = pdb_list[pdb_count] @@ -204,25 +221,22 @@ def retreive_ligand_and_env( prepped_pdb_fnames = set() for idx, row in rows.iterrows(): sys.stdout.flush() - binding_site_counter = ( - row["receptor_chain"] + row["binding_site_number_code"] - ) + bs_counter = row["receptor_chain"] + row["binding_site_number_code"] + if (pdb_id, bs_counter) in done_list: + continue try: st, fname = get_prepped_protein(pdb_id, row, fill_sidechain) - except OnlyCAError: - print(f"Error on {pdb_id}: Structure has only CA") - continue except RuntimeError as e: - print(f"Error on {pdb_id}: PrepWizard failed") + print(f"Error on {pdb_id}, {bs_counter}: PrepWizard failed") print(e) continue except ConnectionError: print( - f"Error on {pdb_id}: Could not reach PDB server, try again later?" + f"Error on {pdb_id}, {bs_counter}: Could not reach PDB server, try again later?" ) continue except ValueError: - print(f"Error on {pdb_id}: BioLiP chain error") + print(f"Error on {pdb_id}, {bs_counter}: BioLiP chain error") continue else: prepped_pdb_fnames.add(fname) @@ -230,16 +244,14 @@ def retreive_ligand_and_env( try: lig_ats, res_ats = get_atom_lists(st, row) except MissingAtomsError: - print(f"Error on {pdb_id}, {binding_site_counter}: Atoms are missing") + print(f"Error on {pdb_id}, {bs_counter}: Atoms are missing") continue except MissingResiduesError as e: - print( - f"Error on {pdb_id}, {binding_site_counter}: {e} residue is missing" - ) + print(f"Error on {pdb_id}, {bs_counter}: {e} residue is missing") continue except MutateError: print( - f"Error on {pdb_id}, {binding_site_counter}: Cannot mutate gap residue to GLY" + f"Error on {pdb_id}, {bs_counter}: Cannot mutate gap residue to GLY" ) continue @@ -250,18 +262,18 @@ def retreive_ligand_and_env( continue # Do the extraction - print(f"obtaining {pdb_id}, binding site {binding_site_counter}") + print(f"obtaining {pdb_id}, binding site {bs_counter}") ligand_env = st.extract(lig_ats + res_ats) try: cap_termini(st, ligand_env) except Exception as e: - print(f"Error on {pdb_id}, {binding_site_counter}: Cannot cap termini") + print(f"Error on {pdb_id}, {bs_counter}: Cannot cap termini") print(e) continue ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) fname = os.path.join( output_path, - f"{pdb_id}_{binding_site_counter}_{ligand_env.formal_charge}.pdb", + f"{pdb_id}_{bs_counter}_{ligand_env.formal_charge}.pdb", ) ligand_env.write(fname) @@ -271,28 +283,34 @@ def retreive_ligand_and_env( os.remove(fname) -def download_cif(pdb_id: str, chains: List[str]) -> str: +def download_cif(pdb_id: str) -> Structure: """ Download cif (as opposed to pdb) of a given protein and extract the needed chains. :param pdb_id: name of PDB to download - :param chains: list of relevant chain names to extract - :return: filename where structure has been downloaded + :return: Downloaded structure """ - cif_name = f"{pdb_id}.cif" + fname = f"{pdb_id}.cif" for i in range(3): subprocess.run( [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] ) - if os.path.exists(cif_name): + if os.path.exists(fname): break else: time.sleep(10) else: raise ConnectionError - return cif_name + try: + st = next(StructureReader(fname), None) + except IndexError: + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) + st = next(StructureReader(f"{pdb_id}.pdb"), None) + if st is None: + raise ConnectionError + return st def get_prepped_protein( @@ -316,7 +334,7 @@ def get_prepped_protein( """ chains = {row["receptor_chain"], row["ligand_chain"]} outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" - fname = f"{pdb_id}.pdb" + fname = f"{pdb_id}.cif" maename = f"{pdb_id}.maegz" if not prep: @@ -327,18 +345,17 @@ def get_prepped_protein( pass else: # We haven't done anything to prepare the protein - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) - if not os.path.exists(fname): - # PDB could not be downloaded, try the cif - fname = download_cif(pdb_id, chains) + st = download_cif(pdb_id) - st = next(StructureReader(fname), None) - if st is None: - raise ValueError - # only extract the relevant chains because these proteins tend to be very large and PrepWizard takes hours + # only extract the relevant chains because these proteins can be large + # and then PrepWizard can take hours at_list = [] - for chain in chains: - at_list.extend(st.chain[chain].getAtomList()) + try: + for chain in chains: + at_list.extend(st.chain[chain].getAtomList()) + except KeyError: + print(f"Chain is missing from {pdb_id}") + raise ValueError st = st.extract(at_list) # Remove any dummy atoms, PrepWizard doesn't like them @@ -548,7 +565,11 @@ def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[ :return: list of residues which are single-residue gaps in `res_list` """ parent_indices = set() - parent_list = list(st.chain[rec_chain].residue) + try: + parent_list = list(st.chain[rec_chain].residue) + except KeyError: + print(f"missing expected receptor chain: {rec_chain}") + raise MissingResiduesError("Chain") for res_name in res_list: try: res = st.findResidue(f"{rec_chain}:{res_name}") From c48f21e99bebe8e63bce6e10c0b74f247eb6cf9f Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 8 Jul 2024 20:35:19 +0000 Subject: [PATCH 085/117] Take PDBs first over CIFs --- biomolecules/pdb_pockets/biolip_extraction.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 17aa8c8..5a4f466 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -291,6 +291,17 @@ def download_cif(pdb_id: str) -> Structure: :param pdb_id: name of PDB to download :return: Downloaded structure """ + + # Try for the PDB + fname = f"{pdb_id}.pdb" + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) + if os.path.exists(fname): + st = next(StructureReader(fname), None) + os.remove(fname) + if st is not None: + return st + + # Failing that, take the CIF fname = f"{pdb_id}.cif" for i in range(3): subprocess.run( @@ -303,11 +314,7 @@ def download_cif(pdb_id: str) -> Structure: else: raise ConnectionError - try: - st = next(StructureReader(fname), None) - except IndexError: - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) - st = next(StructureReader(f"{pdb_id}.pdb"), None) + st = next(StructureReader(fname), None) if st is None: raise ConnectionError return st From 3e65d581448eafc0becbd382e0f5a6457b6319ad Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 9 Jul 2024 17:29:30 +0000 Subject: [PATCH 086/117] speedups for are_conformers --- electrolytes/solvation_shell_extract.py | 83 +++++++++++++++++-------- 1 file changed, 56 insertions(+), 27 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 17ae4b4..61a3005 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -9,6 +9,7 @@ import json import argparse import numpy as np +from collections import Counter from schrodinger.structure import StructureReader from schrodinger.structutils import analyze @@ -78,14 +79,12 @@ def extract_solvation_shells( solvent_resnames = set(solvents.values()) # Read a structure - structures = StructureReader(os.path.join(input_dir, "system_output.pdb")) - + structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[:10] # assign partial charges to atoms - # TODO: fix this - the iterator over structures can only be called once - # logging.info("Assigning partial charges to atoms") - # for st in tqdm(structures): - # for at, charge in zip(st.atom, partial_charges): - # at.partial_charge = charge + logging.info("Assigning partial charges to atoms") + for st in tqdm(structures): + for at, charge in zip(st.atom, partial_charges): + at.partial_charge = charge # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin @@ -94,7 +93,7 @@ def extract_solvation_shells( for radius in solute_radii: logging.info(f"Radius = {radius} A") expanded_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps + for i, st in tqdm(enumerate(structures), total=len(structures)): # loop over timesteps # extract all solute molecules solute_molecules = [ @@ -136,16 +135,13 @@ def extract_solvation_shells( solute_resnames, max_shell_size=upper_bound, ) - expanded_shell_ats = sorted(expanded_shell_ats) + #expanded_shell_ats = sorted(expanded_shell_ats) + central_at = st.molecule[central_solute].atom[1] + central_at.property['b_m_central'] = True expanded_shell = st.extract(expanded_shell_ats, copy_props=True) # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_atom_idx = ( - expanded_shell_ats.index( - st.molecule[central_solute].getAtomList()[0] - ) - + 1 - ) + central_solute_atom_idx = next(at for at in expanded_shell.atom if at.property.pop('b_m_central', False)).index # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) @@ -161,7 +157,10 @@ def extract_solvation_shells( # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") # TODO: speed this up - grouped_shells = group_with_comparison(expanded_shells, are_conformers) + isomeric_shells = group_with_comparison(expanded_shells, are_isomeric_molecules) + grouped_shells = [] + for isomer_group in isomeric_shells: + grouped_shells.extend(groupby_molecules_are_conformers(isomer_group)) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [ @@ -172,7 +171,7 @@ def extract_solvation_shells( logging.info(f"Extracting top {top_n} most diverse shells from each group") final_shells = [] # example grouping - set of structures - for group_idx, shell_group in tqdm(enumerate(grouped_shells)): + for group_idx, shell_group in tqdm(enumerate(grouped_shells), total=len(grouped_shells)): filtered = filter_by_rmsd(shell_group, n=top_n) filtered = [(group_idx, st) for st in filtered] final_shells.extend(filtered) @@ -183,6 +182,7 @@ def extract_solvation_shells( os.makedirs(save_path, exist_ok=True) for i, (group_idx, st) in enumerate(final_shells): # TODO: seems like this is saving an extra line at the end of the xyz files + # DSL: So what? st.write(os.path.join(save_path, f"group_{group_idx}" f"shell_{i}.xyz")) if not skip_solvent_centered_shells: @@ -192,11 +192,7 @@ def extract_solvation_shells( for radius in solvent_radii: logging.info(f"Radius = {radius} A") filtered_shells = [] - for i, st in tqdm(enumerate(structures)): # loop over timesteps - # assign partial charges to atoms - for at, charge in zip(st.atom, partial_charges): - at.partial_charge = charge - + for i, st in tqdm(enumerate(structures), total=len(structures)): # loop over timesteps # extract all solvent molecules solvent_molecules = [ res for res in st.residue if res.pdbres.strip() == residue @@ -233,9 +229,7 @@ def extract_solvation_shells( filtered_shells.extend(size_filtered_shells) # Choose a random subset of shells - assert ( - len(filtered_shells) > 0 - ), "No solute-free shells found for solvent" + assert filtered_shells, "No solute-free shells found for solvent" # check that every shell is below the max size for shell in filtered_shells: assert ( @@ -247,8 +241,7 @@ def extract_solvation_shells( # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") - # TODO: speed this up - grouped_shells = group_with_comparison(filtered_shells, are_conformers) + grouped_shells = group_with_comparison(filtered_shells, are_isomeric_molecules) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [ @@ -275,6 +268,42 @@ def extract_solvation_shells( # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) +def are_isomeric_molecules(st1, st2): + isomers = st1.mol_total == st2.mol_total and st1.atom_total == st2.atom_total + if isomers: + cnt1 = {frozenset(Counter(mol.atom).items()) for mol in st1.molecule} + cnt2 = {frozenset(Counter(mol.atom).items()) for mol in st2.molecule} + isomers = cnt1 == cnt2 + return isomers + +def groupby_molecules_are_conformers(st_list): + def are_same_group_counts(group1, group2): + return {count for count, _ in group1} == {count for count, _ in group2} + + def are_groups_conformers(group1, group2): + matched_groups = 0 + for count1, st1 in group1: + for count2, st2 in group2: + if count1 == count2 and are_conformers(st1, st2): + matched_groups += 1 + break + return matched_groups == len(group1) + + mol_to_st = {} + for st in st_list: + mol_list = [mol.extractStructure() for mol in st.molecule] + mol_list.sort(key=lambda x: x.atom_total) + grouped_mol_list = group_with_comparison(mol_list, are_conformers) + st_mols = frozenset((len(grp), grp[0]) for grp in grouped_mol_list) + mol_to_st[st_mols] = st + + grouped_by_molecular_counts = group_with_comparison(mol_to_st.keys(), are_same_group_counts) + conf_groups = [] + for groups in grouped_by_molecular_counts: + conf_groups.extend(group_with_comparison(groups, are_groups_conformers)) + conf_groups = [[mol_to_st[grp] for grp in cgroup] for cgroup in conf_groups] + return conf_groups + if __name__ == "__main__": logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO")) From 0e54a944e801cca26da72a9840f4a582cba40651 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 9 Jul 2024 20:03:54 +0000 Subject: [PATCH 087/117] cleanup --- electrolytes/solvation_shell_extract.py | 103 +++++++++++++++--------- 1 file changed, 65 insertions(+), 38 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 61a3005..031464c 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -79,7 +79,7 @@ def extract_solvation_shells( solvent_resnames = set(solvents.values()) # Read a structure - structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[:10] + structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb"))) # assign partial charges to atoms logging.info("Assigning partial charges to atoms") for st in tqdm(structures): @@ -93,7 +93,9 @@ def extract_solvation_shells( for radius in solute_radii: logging.info(f"Radius = {radius} A") expanded_shells = [] - for i, st in tqdm(enumerate(structures), total=len(structures)): # loop over timesteps + for i, st in tqdm( + enumerate(structures), total=len(structures) + ): # loop over timesteps # extract all solute molecules solute_molecules = [ @@ -135,13 +137,16 @@ def extract_solvation_shells( solute_resnames, max_shell_size=upper_bound, ) - #expanded_shell_ats = sorted(expanded_shell_ats) central_at = st.molecule[central_solute].atom[1] - central_at.property['b_m_central'] = True + central_at.property["b_m_central"] = True expanded_shell = st.extract(expanded_shell_ats, copy_props=True) # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_atom_idx = next(at for at in expanded_shell.atom if at.property.pop('b_m_central', False)).index + central_solute_atom_idx = next( + at + for at in expanded_shell.atom + if at.property.pop("b_m_central", False) + ).index # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) @@ -157,7 +162,9 @@ def extract_solvation_shells( # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") # TODO: speed this up - isomeric_shells = group_with_comparison(expanded_shells, are_isomeric_molecules) + isomeric_shells = group_with_comparison( + expanded_shells, are_isomeric_molecules + ) grouped_shells = [] for isomer_group in isomeric_shells: grouped_shells.extend(groupby_molecules_are_conformers(isomer_group)) @@ -171,7 +178,9 @@ def extract_solvation_shells( logging.info(f"Extracting top {top_n} most diverse shells from each group") final_shells = [] # example grouping - set of structures - for group_idx, shell_group in tqdm(enumerate(grouped_shells), total=len(grouped_shells)): + for group_idx, shell_group in tqdm( + enumerate(grouped_shells), total=len(grouped_shells) + ): filtered = filter_by_rmsd(shell_group, n=top_n) filtered = [(group_idx, st) for st in filtered] final_shells.extend(filtered) @@ -192,7 +201,9 @@ def extract_solvation_shells( for radius in solvent_radii: logging.info(f"Radius = {radius} A") filtered_shells = [] - for i, st in tqdm(enumerate(structures), total=len(structures)): # loop over timesteps + for i, st in tqdm( + enumerate(structures), total=len(structures) + ): # loop over timesteps # extract all solvent molecules solvent_molecules = [ res for res in st.residue if res.pdbres.strip() == residue @@ -241,7 +252,9 @@ def extract_solvation_shells( # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") - grouped_shells = group_with_comparison(filtered_shells, are_isomeric_molecules) + grouped_shells = group_with_comparison( + filtered_shells, are_isomeric_molecules + ) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [ @@ -268,41 +281,55 @@ def extract_solvation_shells( # TODO: seems like this is saving an extra line at the end of the xyz files st.write(os.path.join(save_path, f"shell_{i}.xyz")) + def are_isomeric_molecules(st1, st2): - isomers = st1.mol_total == st2.mol_total and st1.atom_total == st2.atom_total + isomers = st1.atom_total == st2.atom_total and st1.mol_total == st2.mol_total + if isomers: + isomers = Counter(at.atomic_number for at in st1.atom) == Counter( + at.atomic_number for at in st2.atom + ) if isomers: - cnt1 = {frozenset(Counter(mol.atom).items()) for mol in st1.molecule} - cnt2 = {frozenset(Counter(mol.atom).items()) for mol in st2.molecule} + cnt1 = { + frozenset(Counter(at.atomic_number for at in mol.atom).items()) + for mol in st1.molecule + } + cnt2 = { + frozenset(Counter(at.atomic_number for at in mol.atom).items()) + for mol in st2.molecule + } isomers = cnt1 == cnt2 return isomers + def groupby_molecules_are_conformers(st_list): - def are_same_group_counts(group1, group2): - return {count for count, _ in group1} == {count for count, _ in group2} - - def are_groups_conformers(group1, group2): - matched_groups = 0 - for count1, st1 in group1: - for count2, st2 in group2: - if count1 == count2 and are_conformers(st1, st2): - matched_groups += 1 - break - return matched_groups == len(group1) - - mol_to_st = {} - for st in st_list: - mol_list = [mol.extractStructure() for mol in st.molecule] - mol_list.sort(key=lambda x: x.atom_total) - grouped_mol_list = group_with_comparison(mol_list, are_conformers) - st_mols = frozenset((len(grp), grp[0]) for grp in grouped_mol_list) - mol_to_st[st_mols] = st - - grouped_by_molecular_counts = group_with_comparison(mol_to_st.keys(), are_same_group_counts) - conf_groups = [] - for groups in grouped_by_molecular_counts: - conf_groups.extend(group_with_comparison(groups, are_groups_conformers)) - conf_groups = [[mol_to_st[grp] for grp in cgroup] for cgroup in conf_groups] - return conf_groups + def are_same_group_counts(group1, group2): + return {count for count, _ in group1} == {count for count, _ in group2} + + def are_groups_conformers(group1, group2): + matched_groups = 0 + for count1, st1 in group1: + for count2, st2 in group2: + if count1 == count2 and are_conformers(st1, st2): + matched_groups += 1 + break + return matched_groups == len(group1) + + mol_to_st = {} + for st in st_list: + mol_list = [mol.extractStructure() for mol in st.molecule] + mol_list.sort(key=lambda x: x.atom_total) + grouped_mol_list = group_with_comparison(mol_list, are_conformers) + st_mols = frozenset((len(grp), grp[0]) for grp in grouped_mol_list) + mol_to_st[st_mols] = st + + grouped_by_molecular_counts = group_with_comparison( + mol_to_st.keys(), are_same_group_counts + ) + conf_groups = [] + for groups in grouped_by_molecular_counts: + conf_groups.extend(group_with_comparison(groups, are_groups_conformers)) + conf_groups = [[mol_to_st[grp] for grp in cgroup] for cgroup in conf_groups] + return conf_groups if __name__ == "__main__": From 3966421058b65006a0aec8ba086d10a22d9e07df Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 10 Jul 2024 00:45:03 +0000 Subject: [PATCH 088/117] some logging, restrict to 100 frames for now --- electrolytes/solvation_shell_extract.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 031464c..5566548 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -79,7 +79,7 @@ def extract_solvation_shells( solvent_resnames = set(solvents.values()) # Read a structure - structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb"))) + structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[:100] # assign partial charges to atoms logging.info("Assigning partial charges to atoms") for st in tqdm(structures): @@ -150,7 +150,7 @@ def extract_solvation_shells( # contract everthing to be centered on our molecule of interest # (this will also handle if a molecule is split across a PBC) - clusterstruct.contract_structure2( + clusterstruct.contract_structure( expanded_shell, contract_on_atoms=[central_solute_atom_idx] ) assert ( @@ -165,8 +165,9 @@ def extract_solvation_shells( isomeric_shells = group_with_comparison( expanded_shells, are_isomeric_molecules ) + logging.info("Grouped into isomers") grouped_shells = [] - for isomer_group in isomeric_shells: + for isomer_group in tqdm(isomeric_shells): grouped_shells.extend(groupby_molecules_are_conformers(isomer_group)) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) From c877a8b4003463b9bcf137a4bf50018d64e032da Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 10 Jul 2024 00:51:20 +0000 Subject: [PATCH 089/117] basic docstrings --- electrolytes/solvation_shell_extract.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 5566548..21f729f 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -284,6 +284,13 @@ def extract_solvation_shells( def are_isomeric_molecules(st1, st2): + """ + Determine if two structures have molecules which are isomers of each other. + + This is stronger than just ensuring that the structures are isomers and should + be sufficient for cases of just solvents as there are no expected topological + differences. + """ isomers = st1.atom_total == st2.atom_total and st1.mol_total == st2.mol_total if isomers: isomers = Counter(at.atomic_number for at in st1.atom) == Counter( @@ -303,6 +310,10 @@ def are_isomeric_molecules(st1, st2): def groupby_molecules_are_conformers(st_list): + """ + Given a list of Structures which are assumed to have isomeric molecules, + partition the structures by conformers. + """ def are_same_group_counts(group1, group2): return {count for count, _ in group1} == {count for count, _ in group2} From 29634805110a9e77b1b60cd4bf546daea37fb227 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 10 Jul 2024 18:07:53 +0000 Subject: [PATCH 090/117] refactor into separate functions, re-use code --- electrolytes/solvation_shell_extract.py | 414 +++++++++++++----------- electrolytes/solvation_shell_utils.py | 31 +- 2 files changed, 232 insertions(+), 213 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 21f729f..a25dc52 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -1,30 +1,29 @@ -from typing import List import logging +from typing import List logging.basicConfig(level=logging.INFO) -import random -import os -from tqdm import tqdm -import json import argparse -import numpy as np +import json +import os +import random from collections import Counter -from schrodinger.structure import StructureReader +import numpy as np +from schrodinger.application.jaguar.utils import group_with_comparison +from schrodinger.application.matsci import clusterstruct +from schrodinger.comparison import are_conformers +from schrodinger.structure import Structure, StructureReader from schrodinger.structutils import analyze +from tqdm import tqdm + from solvation_shell_utils import ( expand_shell, - renumber_molecules_to_match, filter_by_rmsd, - filter_shells_with_solute_atoms, generate_lognormal_samples, + renumber_molecules_to_match, ) from utils import validate_metadata_file -from schrodinger.comparison import are_conformers -from schrodinger.application.jaguar.utils import group_with_comparison -from schrodinger.application.matsci import clusterstruct -from schrodinger.structutils import rmsd def extract_solvation_shells( @@ -55,7 +54,6 @@ def extract_solvation_shells( """ # Read a structure and metadata file - # TODO: add charges logging.info("Reading structure and metadata files") # Read metadata @@ -68,18 +66,21 @@ def extract_solvation_shells( solutes = {} solvents = {} - for res, species, type in zip( + for res, species, spec_type in zip( metadata["residue"], metadata["species"], metadata["solute_or_solvent"] ): - if type == "solute": + if spec_type == "solute": solutes[species] = res - elif type == "solvent": + elif spec_type == "solvent": solvents[species] = res + spec_dicts = {"solute": solutes, "solvent": solvents} solute_resnames = set(solutes.values()) solvent_resnames = set(solvents.values()) - # Read a structure - structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[:100] + # Read structures + structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[ + :100 + ] # assign partial charges to atoms logging.info("Assigning partial charges to atoms") for st in tqdm(structures): @@ -88,174 +89,41 @@ def extract_solvation_shells( # For each solute: extract shells around the solute of some heuristic radii and bin by composition/graph hash # Choose the N most diverse in each bin - for species, residue in solutes.items(): - logging.info(f"Extracting solvation shells around {species}") - for radius in solute_radii: - logging.info(f"Radius = {radius} A") - expanded_shells = [] - for i, st in tqdm( - enumerate(structures), total=len(structures) - ): # loop over timesteps - - # extract all solute molecules - solute_molecules = [ - res for res in st.residue if res.pdbres.strip() == residue - ] - - # Subsample a random set of k solute molecules - if shells_per_frame > 0: - solute_molecules = random.sample(solute_molecules, shells_per_frame) - - central_solute_nums = [mol.molecule_number for mol in solute_molecules] - # Extract solvation shells - shells = [ - set( - analyze.evaluate_asl( - st, f"fillres within {radius} mol {mol_num}" - ) - ) - for mol_num in central_solute_nums - ] + spec_types = ["solute"] + if not skip_solvent_centered_shells: + spec_types.append("solvent") - # Now expand the shells - for shell_ats, central_solute in zip(shells, central_solute_nums): - expanded_shell_ats = shell_ats - # If we have a solvent-free system, don't expand shells around solutes, - # because we'll always have solutes and will never terminate - if solvent_resnames: - # TODO: how to choose the mean/scale for sampling? - # Should the mean be set to the number of atoms in the non-expanded shell? - upper_bound = max( - len(shell_ats), generate_lognormal_samples()[0] - ) - upper_bound = min(upper_bound, max_shell_size) - expanded_shell_ats = expand_shell( + for spec_type in spec_types: + for species, residue in spec_dicts[spec_type].items(): + logging.info(f"Extracting solvation shells around {species}") + for radius in solute_radii: + logging.info(f"Radius = {radius} A") + extracted_shells = [] + for i, st in tqdm( + enumerate(structures), total=len(structures) + ): # loop over timesteps + extracted_shells.extend( + extract_residue_from_structure( st, - shell_ats, - central_solute, radius, + residue, + spec_type, solute_resnames, - max_shell_size=upper_bound, + solvent_resnames, + shells_per_frame, + max_shell_size, ) - central_at = st.molecule[central_solute].atom[1] - central_at.property["b_m_central"] = True - expanded_shell = st.extract(expanded_shell_ats, copy_props=True) - - # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) - central_solute_atom_idx = next( - at - for at in expanded_shell.atom - if at.property.pop("b_m_central", False) - ).index - - # contract everthing to be centered on our molecule of interest - # (this will also handle if a molecule is split across a PBC) - clusterstruct.contract_structure( - expanded_shell, contract_on_atoms=[central_solute_atom_idx] ) - assert ( - expanded_shell.atom_total <= max_shell_size - ), "Expanded shell too large" - expanded_shells.append(expanded_shell) - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - # TODO: speed this up - isomeric_shells = group_with_comparison( - expanded_shells, are_isomeric_molecules - ) - logging.info("Grouped into isomers") - grouped_shells = [] - for isomer_group in tqdm(isomeric_shells): - grouped_shells.extend(groupby_molecules_are_conformers(isomer_group)) - - # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) - grouped_shells = [ - renumber_molecules_to_match(items) for items in grouped_shells - ] - - # Now extract the top N most diverse shells from each group - logging.info(f"Extracting top {top_n} most diverse shells from each group") - final_shells = [] - # example grouping - set of structures - for group_idx, shell_group in tqdm( - enumerate(grouped_shells), total=len(grouped_shells) - ): - filtered = filter_by_rmsd(shell_group, n=top_n) - filtered = [(group_idx, st) for st in filtered] - final_shells.extend(filtered) - - # Save the final shells - logging.info(f"Saving final shells") - save_path = os.path.join(save_dir, system_name, species, f"radius_{radius}") - os.makedirs(save_path, exist_ok=True) - for i, (group_idx, st) in enumerate(final_shells): - # TODO: seems like this is saving an extra line at the end of the xyz files - # DSL: So what? - st.write(os.path.join(save_path, f"group_{group_idx}" f"shell_{i}.xyz")) - if not skip_solvent_centered_shells: - # Now repeat for solvents to capture solvent-solvent interactions - for species, residue in solvents.items(): - logging.info(f"Extracting shells around {species}") - for radius in solvent_radii: - logging.info(f"Radius = {radius} A") - filtered_shells = [] - for i, st in tqdm( - enumerate(structures), total=len(structures) - ): # loop over timesteps - # extract all solvent molecules - solvent_molecules = [ - res for res in st.residue if res.pdbres.strip() == residue - ] - - # Subsample a random set of k solvent molecules - if shells_per_frame > 0: - solvent_molecules = random.sample( - solvent_molecules, shells_per_frame - ) - central_solvent_nums = [ - mol.molecule_number for mol in solvent_molecules - ] - - # Extract solvation shells - shells = [ - set( - analyze.evaluate_asl( - st, f"fillres within {radius} mol {mol_num}" - ) - ) - for mol_num in central_solvent_nums - ] + if spec_type == "solvent": + assert extracted_shells, "No solute-free shells found for solvent" + # DSL: Is the really an assertion error? Or just sad but we should soldier on (i.e. continue) - # Only keep the shells that have no solute atoms and below a maximum size - solute_free_shells = filter_shells_with_solute_atoms( - shells, st, solute_resnames - ) - size_filtered_shells = [ - shell - for shell in solute_free_shells - if shell.atom_total <= max_shell_size - ] - filtered_shells.extend(size_filtered_shells) - - # Choose a random subset of shells - assert filtered_shells, "No solute-free shells found for solvent" - # check that every shell is below the max size - for shell in filtered_shells: - assert ( - shell.atom_total <= max_shell_size - ), "Expanded shell too large" - random.shuffle(filtered_shells) - filtered_shells = filtered_shells[:1000] - - # Now compare the expanded shells and group them by similarity - # we will get lists of lists of shells where each list of structures are conformers of each other - logging.info("Grouping solvation shells into conformers") - grouped_shells = group_with_comparison( - filtered_shells, are_isomeric_molecules - ) + # Choose a random subset of shells + random.shuffle(extracted_shells) + extracted_shells = extracted_shells[:1000] + + grouped_shells = group_shells(extracted_shells, spec_type) # Now ensure that topologically related atoms are equivalently numbered (up to molecular symmetry) grouped_shells = [ @@ -268,22 +136,188 @@ def extract_solvation_shells( ) final_shells = [] # example grouping - set of structures - for shell_group in tqdm(grouped_shells): + for group_idx, shell_group in tqdm( + enumerate(grouped_shells), total=len(grouped_shells) + ): filtered = filter_by_rmsd(shell_group, n=top_n) + filtered = [(group_idx, st) for st in filtered] final_shells.extend(filtered) # Save the final shells - logging.info(f"Saving final shells") + logging.info("Saving final shells") save_path = os.path.join( save_dir, system_name, species, f"radius_{radius}" ) os.makedirs(save_path, exist_ok=True) - for i, st in enumerate(final_shells): + for i, (group_idx, st) in enumerate(final_shells): + charge = get_structure_charge(st) + if spec_type == "solute": + fname = os.path.join( + save_path, f"group_{group_idx}", f"shell_{i}_{charge}.xyz" + ) + elif spec_type == "solvent": + fname = os.path.join(save_path, f"shell_{i}_{charge}.xyz") + # TODO: seems like this is saving an extra line at the end of the xyz files - st.write(os.path.join(save_path, f"shell_{i}.xyz")) + # DSL: So what? + st.write(fname) + + +def extract_residue_from_structure( + st: Structure, + radius: float, + residue: str, + spec_type: str, + solute_resnames: list[str], + solvent_resnames: list[str], + shells_per_frame: int, + max_shell_size: int, +) -> Structure: + """ + Extract around a given residue type from a structure by a given radius + + :param st: Structure to extract from + :param radius: distance (in Angstrom) around residue to expand + (initially in the case of solutes) + :param resiude: name of residue to consider + :param spec_type: type of species being extracted, either 'solute' or 'solvent' + :param solute_resnames: list of names of solute residues + :param solvent_resnames: list of names of solvent residues + :param shells_per_frame: number of shells to extract from this structure + :param max_shell_size: maximum number of atoms in a shell + :return: extracted shell structure + """ + # extract all molecules of interest + molecules = [res for res in st.residue if res.pdbres.strip() == residue] + + # Subsample a random set of k solute molecules + if shells_per_frame > 0: + molecules = random.sample(molecules, shells_per_frame) + + central_mol_nums = list({mol.molecule_number for mol in molecules}) + # Extract solvation shells + shells = [ + set(analyze.evaluate_asl(st, f"fillres within {radius} mol {mol_num}")) + for mol_num in central_mol_nums + ] + + if spec_type == "solvent": + # Only keep the shells that have no solute atoms and below a maximum size + solute_atoms = analyze.evaluate_asl(st, f'res {",".join(solute_resnames)}') + shells = [ + shell + for shell in shells + if (not shell.intersection(solute_atoms)) + and shell.atom_total <= max_shell_size + ] + extracted_shells = [ + extract_contracted_shell(st, at_list, central_mol) + for at_list, central_mol in zip(shells, central_mol_nums) + ] + + elif spec_type == "solute": + extracted_shells = [] + for shell_ats, central_solute in zip(shells, central_mol_nums): + # Now expand the shells + expanded_shell_ats = shell_ats + # If we have a solvent-free system, don't expand shells around solutes, + # because we'll always have solutes and will never terminate + if solvent_resnames: + # TODO: how to choose the mean/scale for sampling? + # Should the mean be set to the number of atoms in the non-expanded shell? + upper_bound = max(len(shell_ats), generate_lognormal_samples()[0]) + upper_bound = min(upper_bound, max_shell_size) + expanded_shell_ats = expand_shell( + st, + shell_ats, + central_solute, + radius, + solute_resnames, + max_shell_size=upper_bound, + ) + expanded_shell = extract_contracted_shell( + st, expanded_shell_ats, central_solute + ) + assert ( + expanded_shell.atom_total <= max_shell_size + ), "Expanded shell too large" + extracted_shells.append(expanded_shell) + return extracted_shells -def are_isomeric_molecules(st1, st2): + +def extract_contracted_shell( + st: Structure, at_list: list[int], central_mol: int +) -> Structure: + """ + Extract the shell from the structure + + :param st: structure to extract from + :param at_list: list of atom indices that specify shell + :param central_mol: index of central molecule around which we should contract + with respect to PBC to get a non-PBC valid structure + :return: extracted shell + """ + central_at = st.molecule[central_mol].atom[1] + central_at.property["b_m_central"] = True + extracted_shell = st.extract(at_list, copy_props=True) + central_at.property.pop("b_m_central") + + # find index of first atom of the central solute in the sorted shell_ats (adjust for 1-indexing) + central_atom_idx = next( + at for at in extracted_shell.atom if at.property.pop("b_m_central", False) + ).index + + # contract everthing to be centered on our molecule of interest + # (this will also handle if a molecule is split across a PBC) + clusterstruct.contract_structure( + extracted_shell, contract_on_atoms=[central_atom_idx] + ) + return extracted_shell + + +def group_shells(shell_list: list[Structure], spec_type: str) -> list[list[Structure]]: + """ + Partition shells by conformers. + + This checks the topological similarity of the shells to group them. For solvents, + we don't check this topology explicitly but assume it holds if the molecules are + at least isomers of each other. Revise if we have solvent mixtures where the + components are isomers + + :param shell_list: list of structures to be partitioned + :param spec_type: type of species being grouped, either 'solute' or 'solvent' + :return: members of `shell_list` grouped by conformers, all members of a given + sublist are conformers + """ + # Now compare the expanded shells and group them by similarity + # we will get lists of lists of shells where each list of structures are conformers of each other + logging.info("Grouping solvation shells into conformers") + # TODO: speed this up + grouped_shells = group_with_comparison(shell_list, are_isomeric_molecules) + logging.info("Grouped into isomers") + + if spec_type == "solute": + new_grouped_shells = [] + for isomer_group in tqdm(grouped_shells): + new_grouped_shells.extend(groupby_molecules_are_conformers(isomer_group)) + grouped_shells = new_grouped_shells + return grouped_shells + + +def get_structure_charge(st: Structure) -> int: + """ + Get the charge on the structure as the sum of the partial charges + of the atoms + + :param st: Structure to get charge of + :return: charge on structure + """ + charge = sum(at.partial_charge for at in st.atom) + return round(charge) + + +def are_isomeric_molecules(st1: Structure, st2: Structure) -> bool: """ Determine if two structures have molecules which are isomers of each other. @@ -309,11 +343,12 @@ def are_isomeric_molecules(st1, st2): return isomers -def groupby_molecules_are_conformers(st_list): +def groupby_molecules_are_conformers(st_list: list[Structure]) -> list[list[Structure]]: """ Given a list of Structures which are assumed to have isomeric molecules, partition the structures by conformers. """ + def are_same_group_counts(group1, group2): return {count for count, _ in group1} == {count for count, _ in group2} @@ -326,18 +361,27 @@ def are_groups_conformers(group1, group2): break return matched_groups == len(group1) + if len(st_list) == 1: + return [st_list] + mol_to_st = {} + # split structures up into lists of molecules for st in st_list: mol_list = [mol.extractStructure() for mol in st.molecule] mol_list.sort(key=lambda x: x.atom_total) + # group those molecules by conformers grouped_mol_list = group_with_comparison(mol_list, are_conformers) + # represent the structure as the counts of each type of molecule + # and a representative structure st_mols = frozenset((len(grp), grp[0]) for grp in grouped_mol_list) mol_to_st[st_mols] = st + # Group structures by if their counts of molecules are the same grouped_by_molecular_counts = group_with_comparison( mol_to_st.keys(), are_same_group_counts ) conf_groups = [] + # Group structures by if their molecules (and their counts) are conformers for groups in grouped_by_molecular_counts: conf_groups.extend(group_with_comparison(groups, are_groups_conformers)) conf_groups = [[mol_to_st[grp] for grp in cgroup] for cgroup in conf_groups] diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index 6b19441..dda6f2c 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -1,15 +1,10 @@ -import re -import numpy as np import random -from typing import List, Set, Callable +from typing import List, Set -from schrodinger.structutils import analyze -from schrodinger.application.matsci import clusterstruct -from schrodinger.comparison import are_conformers -from schrodinger.application.jaguar.utils import group_with_comparison +import numpy as np from schrodinger.comparison.atom_mapper import ConnectivityAtomMapper -from schrodinger.structutils import rmsd from schrodinger.structure import Structure +from schrodinger.structutils import analyze, rmsd def generate_lognormal_samples(loc=75, sigma=0.45, size=1): @@ -28,26 +23,6 @@ def generate_lognormal_samples(loc=75, sigma=0.45, size=1): return samples -def filter_shells_with_solute_atoms( - shells: List[Set[int]], st: Structure, solute_res_names: List[str] -) -> List[Structure]: - """ - Filter out shells that contain solute atoms. - Args: - shells: List of sets of atom indices that correspond to shells - st: Entire structure from the PDB file - solute_res_names: List of residue names that correspond to solute atoms in the simulation - Returns: - List of Schrodinger structures that do not contain solute atoms - """ - - solute_atoms = analyze.evaluate_asl(st, f'res {",".join(solute_res_names)}') - filtered_shells = [ - shell for shell in shells if not shell.intersection(solute_atoms) - ] - return [st.extract(shell, copy_props=True) for shell in filtered_shells] - - def expand_shell( st: Structure, shell_ats: Set[int], From f225f376ff10fe58e434947954d5bef5652c8c4d Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 10 Jul 2024 20:30:19 +0000 Subject: [PATCH 091/117] refactor bug --- electrolytes/solvation_shell_extract.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index a25dc52..20e87b9 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -153,7 +153,7 @@ def extract_solvation_shells( charge = get_structure_charge(st) if spec_type == "solute": fname = os.path.join( - save_path, f"group_{group_idx}", f"shell_{i}_{charge}.xyz" + save_path, f"group_{group_idx}_shell_{i}_{charge}.xyz" ) elif spec_type == "solvent": fname = os.path.join(save_path, f"shell_{i}_{charge}.xyz") @@ -205,14 +205,14 @@ def extract_residue_from_structure( # Only keep the shells that have no solute atoms and below a maximum size solute_atoms = analyze.evaluate_asl(st, f'res {",".join(solute_resnames)}') shells = [ - shell - for shell in shells + (shell, central_mol) + for shell, central_mol in zip(shells, central_mol_nums) if (not shell.intersection(solute_atoms)) - and shell.atom_total <= max_shell_size + and len(shell) <= max_shell_size ] extracted_shells = [ extract_contracted_shell(st, at_list, central_mol) - for at_list, central_mol in zip(shells, central_mol_nums) + for at_list, central_mol in shells ] elif spec_type == "solute": From aff9ec2ac683dffbdb0ffd2ddc84d4d091eb0812 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 10 Jul 2024 14:39:27 -0700 Subject: [PATCH 092/117] make solute-free assertion a warning instead --- electrolytes/solvation_shell_extract.py | 38 +++++++------------------ 1 file changed, 11 insertions(+), 27 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 20e87b9..30eb8d0 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -30,9 +30,8 @@ def extract_solvation_shells( input_dir: str, save_dir: str, system_name: str, - solute_radii: List[float], + radii: List[float], skip_solvent_centered_shells: bool, - solvent_radii: List[float], shells_per_frame: int, max_shell_size: int, top_n: int, @@ -45,9 +44,8 @@ def extract_solvation_shells( input_dir: Path to 1) the PDB file containing the MD trajectory (system_output.pdb) and 2) a metadata file (system_metadata.json) save_dir: Directory in which to save extracted solvation shells. system_name: Name of the system - used for naming the save directory. - solute_radii: List of shell radii to extract around solutes. + radii: List of shell radii to extract around solutes and solvents. skip_solvent_centered_shells: Skip extracting solvent-centered shells. - solvent_radii: List of shell radii to extract around solvents. shells_per_frame: Number of solutes or solvents per MD simulation frame from which to extract candidate shells. max_shell_size: Maximum size (in atoms) of saved shells. top_n: Number of snapshots to extract per topology. @@ -78,9 +76,7 @@ def extract_solvation_shells( solvent_resnames = set(solvents.values()) # Read structures - structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb")))[ - :100 - ] + structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb"))) # assign partial charges to atoms logging.info("Assigning partial charges to atoms") for st in tqdm(structures): @@ -96,7 +92,7 @@ def extract_solvation_shells( for spec_type in spec_types: for species, residue in spec_dicts[spec_type].items(): logging.info(f"Extracting solvation shells around {species}") - for radius in solute_radii: + for radius in radii: logging.info(f"Radius = {radius} A") extracted_shells = [] for i, st in tqdm( @@ -116,12 +112,9 @@ def extract_solvation_shells( ) if spec_type == "solvent": - assert extracted_shells, "No solute-free shells found for solvent" - # DSL: Is the really an assertion error? Or just sad but we should soldier on (i.e. continue) - - # Choose a random subset of shells - random.shuffle(extracted_shells) - extracted_shells = extracted_shells[:1000] + # raise a warning and continue to the next radii/species + logging.warning("No solute-free shells found for solvent") + continue grouped_shells = group_shells(extracted_shells, spec_type) @@ -207,8 +200,7 @@ def extract_residue_from_structure( shells = [ (shell, central_mol) for shell, central_mol in zip(shells, central_mol_nums) - if (not shell.intersection(solute_atoms)) - and len(shell) <= max_shell_size + if (not shell.intersection(solute_atoms)) and len(shell) <= max_shell_size ] extracted_shells = [ extract_contracted_shell(st, at_list, central_mol) @@ -409,10 +401,10 @@ def are_groups_conformers(group1, group2): ) parser.add_argument( - "--solute_radii", + "--radii", type=list, default=[3], - help="List of shell radii to extract around solutes", + help="List of shell radii to extract around solutes and solvents", ) parser.add_argument( @@ -421,13 +413,6 @@ def are_groups_conformers(group1, group2): help="Skip extracting solvent-centered shells", ) - parser.add_argument( - "--solvent_radii", - type=list, - default=[3], - help="List of shell radii to extract around solvents", - ) - parser.add_argument( "--shells_per_frame", type=int, @@ -457,9 +442,8 @@ def are_groups_conformers(group1, group2): args.input_dir, args.save_dir, args.system_name, - args.solute_radii, + args.radii, args.skip_solvent_centered_shells, - args.solvent_radii, args.shells_per_frame, args.max_shell_size, args.top_n, From 9657238ec4a9156cea44629b15d8fb4d9e3d8c66 Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 10 Jul 2024 14:48:50 -0700 Subject: [PATCH 093/117] add max frames argument --- electrolytes/run_extraction.sh | 2 +- electrolytes/solvation_shell_extract.py | 14 +++++++++++--- 2 files changed, 12 insertions(+), 4 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index 28cb49d..fd2e72d 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -2,7 +2,7 @@ #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? -$SCHRODINGER/run python3 -m cProfile -o output100.prof solvation_shell_extract.py --input_dir 'testfiles/1' \ +$SCHRODINGER/run python3 solvation_shell_extract.py --input_dir 'testfiles/1' \ --save_dir 'results' \ --system_name 'Li_BF4' \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 30eb8d0..f6490e5 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -32,6 +32,7 @@ def extract_solvation_shells( system_name: str, radii: List[float], skip_solvent_centered_shells: bool, + max_frames: int, shells_per_frame: int, max_shell_size: int, top_n: int, @@ -46,6 +47,7 @@ def extract_solvation_shells( system_name: Name of the system - used for naming the save directory. radii: List of shell radii to extract around solutes and solvents. skip_solvent_centered_shells: Skip extracting solvent-centered shells. + max_frames: Maximum number of frames to read from the trajectory. shells_per_frame: Number of solutes or solvents per MD simulation frame from which to extract candidate shells. max_shell_size: Maximum size (in atoms) of saved shells. top_n: Number of snapshots to extract per topology. @@ -77,6 +79,8 @@ def extract_solvation_shells( # Read structures structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb"))) + if max_frames > 0: + structures = random.sample(structures, max_frames) # assign partial charges to atoms logging.info("Assigning partial charges to atoms") for st in tqdm(structures): @@ -151,8 +155,6 @@ def extract_solvation_shells( elif spec_type == "solvent": fname = os.path.join(save_path, f"shell_{i}_{charge}.xyz") - # TODO: seems like this is saving an extra line at the end of the xyz files - # DSL: So what? st.write(fname) @@ -285,7 +287,6 @@ def group_shells(shell_list: list[Structure], spec_type: str) -> list[list[Struc # Now compare the expanded shells and group them by similarity # we will get lists of lists of shells where each list of structures are conformers of each other logging.info("Grouping solvation shells into conformers") - # TODO: speed this up grouped_shells = group_with_comparison(shell_list, are_isomeric_molecules) logging.info("Grouped into isomers") @@ -413,6 +414,13 @@ def are_groups_conformers(group1, group2): help="Skip extracting solvent-centered shells", ) + parser.add_argument( + "--max_frames", + type=int, + default=-1, + help="Number of MD simulation frames from the trajectory to use for extraction", + ) + parser.add_argument( "--shells_per_frame", type=int, From e0f23218a3bdf197e88789d71a89fe35349b5ced Mon Sep 17 00:00:00 2001 From: Sanjeev Raja Date: Wed, 10 Jul 2024 14:51:42 -0700 Subject: [PATCH 094/117] arg bug --- electrolytes/run_extraction.sh | 4 ++-- electrolytes/solvation_shell_extract.py | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/electrolytes/run_extraction.sh b/electrolytes/run_extraction.sh index fd2e72d..bc9118f 100755 --- a/electrolytes/run_extraction.sh +++ b/electrolytes/run_extraction.sh @@ -1,8 +1,8 @@ #!/bin/bash #TODO: can we automatically extract the names of all the solute atoms from the PDB file so we don't have to re-run this command for each solute? - $SCHRODINGER/run python3 solvation_shell_extract.py --input_dir 'testfiles/1' \ --save_dir 'results' \ - --system_name 'Li_BF4' + --system_name 'Li_BF4' \ + --max_frames 100 \ No newline at end of file diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index f6490e5..0f1451e 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -452,6 +452,7 @@ def are_groups_conformers(group1, group2): args.system_name, args.radii, args.skip_solvent_centered_shells, + args.max_frames, args.shells_per_frame, args.max_shell_size, args.top_n, From dd8e52da80e6ea6aa57a289c243d652480a91ccf Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 15 Jul 2024 20:09:31 +0000 Subject: [PATCH 095/117] update cleanup printing --- biomolecules/pdb_pockets/cleanup.py | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 1d602aa..9eaab2f 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -96,16 +96,20 @@ def main(): try: change_made = remove_ligand_ace_cap(st) or change_made except: - print(fname) - raise + print("Error:", fname) + continue try: change_made = remove_ligand_nma_cap(st) or change_made except: - print(fname) - raise + print("Error:", fname) + continue if change_made: + new_fname = os.path.join(os.path.dirname(fname), '_'.join(os.path.basename(fname).split('_')[:-1])) + new_fname += f'_{st.formal_charge}.pdb' + print(f"{fname} -> {new_fname}") st = build.reorder_protein_atoms_by_sequence(st) - st.write(fname) + os.remove(fname) + st.write(new_fname) if __name__ == "__main__": From 7a05a75e42ea9c9f1924d89e701e906256b8025f Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 15 Jul 2024 23:06:43 +0000 Subject: [PATCH 096/117] delete old files after combining pockets --- biomolecules/pdb_pockets/combine_pockets.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/biomolecules/pdb_pockets/combine_pockets.py b/biomolecules/pdb_pockets/combine_pockets.py index 2acac3f..4c358d7 100644 --- a/biomolecules/pdb_pockets/combine_pockets.py +++ b/biomolecules/pdb_pockets/combine_pockets.py @@ -62,8 +62,8 @@ def combine_pockets(biolip_df: pd.DataFrame, path: str): out_name += f"_{bs_name}" if combined_st is not None: out_name += f"_{combined_st.formal_charge}" - # for fname in old_names: - # os.remove(fname) + for fname in old_names: + os.remove(fname) combined_st.write(os.path.join(path, out_name + ".pdb")) From 23763fb0f59e5887b3b763043564be57cb448350 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 16 Jul 2024 21:26:37 +0000 Subject: [PATCH 097/117] some more cleanup tools --- biomolecules/pdb_pockets/cleanup.py | 126 ++++++++++++++++++++++++++-- 1 file changed, 121 insertions(+), 5 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 9eaab2f..e568f9a 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -3,10 +3,113 @@ import os from schrodinger.structure import Structure, StructureReader -from schrodinger.structutils import analyze, build +from schrodinger.structutils import build, measure +from schrodinger.structutils.analyze import evaluate_asl from tqdm import tqdm +def remove_extra_Hs(st: Structure) -> bool: + ats_to_delete = [] + for pair in measure.get_close_atoms(st, dist=0.5): + at1, at2 = sorted(pair, key=lambda x: st.atom[x].atomic_number) + if ( + st.atom[at1].atomic_number == 1 + and st.atom[at2].atomic_number == 6 + and st.atom[at2].bond_total > 4 + and st.areBound(at1, at2) + ): + ats_to_delete.append(at1) + if ats_to_delete: + st.deleteAtoms(ats_to_delete) + return True + return False + + +def merge_chain_names(st, at1, at2): + chains = [at1.chain, at2.chain] + if len(set(chains)) != 1: + main_chains = [chain for chain in chains if chain.isupper()] + if len(main_chains) == 1: + main_chain = main_chains.pop() + if at1.chain == main_chain: + old_mol = at2.molecule_number + else: + old_mol = at1.molecule_number + old_chain = next(chain for chain in chains if chain != main_chain) + for at in st.molecule[old_mol].atom: + if at.chain == old_chain: + at.chain = main_chain + + +def meld_ace_nma(st): + change_made = False + at_pairs = measure.get_close_atoms(st, dist=0.5) + while at_pairs: + at1, at2 = at_pairs.pop() + at1, at2 = (st.atom[at1], st.atom[at2]) + if ( + {at1.atomic_number, at2.atomic_number} == {6} + and {at1.pdbres.strip(), at2.pdbres.strip()} == {"ACE", "NMA"} + and {at1.pdbname.strip(), at2.pdbname.strip()} == {"CA", "CH3"} + ): + # Renumber chains if necessary + merge_chain_names(st, at1, at2) + + if at1.pdbname.strip() == "CA": + keep_at = at1 + del_at = at2 + else: + keep_at = at2 + del_at = at1 + for at in keep_at.getResidue().getAtomList(): + st.atom[at].resnum = del_at.resnum + st.atom[at].inscode = del_at.inscode + for at in at1.getResidue().getAtomList() + at2.getResidue().getAtomList(): + st.atom[at].pdbres = "GLY " + del_Hs = [b_at for b_at in del_at.bonded_atoms if b_at.atomic_number == 1] + del_Hs.extend( + [b_at for b_at in keep_at.bonded_atoms if b_at.atomic_number == 1] + ) + non_H = next( + b_at for b_at in del_at.bonded_atoms if b_at.atomic_number != 1 + ) + st.addBond(keep_at, non_H, 1) + st.deleteAtoms(del_Hs + [del_at]) + build.add_hydrogens(st, atom_list=[keep_at]) + at_pairs = measure.get_close_atoms(st, dist=0.5) + change_made = True + return change_made + + +def reconnect_open_chains(st: Structure): + broken_C = evaluate_asl( + st, "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2)" + ) + broken_N = evaluate_asl( + st, "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2)" + ) + change_made = False + while broken_C: + change_made = True + b_C = broken_C[0] + for b_N in broken_N: + if st.measure(b_C, b_N) < 1.5: + st.addBond(b_C, b_N, 1) + st.atom[b_C].formal_charge = 0 + st.atom[b_N].formal_charge = 0 + merge_chain_names(st, st.atom[b_C], st.atom[b_N]) + broken_C = evaluate_asl( + st, + "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2)", + ) + broken_N = evaluate_asl( + st, + "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2)", + ) + break + return change_made + + def fix_disrupted_disulfides(st: Structure) -> bool: """ If a cysteine sulfur is missing a hydrogen, add it. @@ -18,7 +121,7 @@ def fix_disrupted_disulfides(st: Structure) -> bool: :param st: Structure to correct :return: If a change was made, return True """ - broken_cysteines = analyze.evaluate_asl(st, "atom.pt SG and atom.att 1") + broken_cysteines = evaluate_asl(st, "atom.pt SG and atom.att 1") if broken_cysteines: build.add_hydrogens(st, atom_list=broken_cysteines) return True @@ -90,7 +193,10 @@ def parse_args(): def main(): args = parse_args() - for fname in tqdm(glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb"))): + file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) + for fname in tqdm(file_list): + if not os.path.exists(fname): + continue st = StructureReader.read(fname) change_made = fix_disrupted_disulfides(st) try: @@ -103,9 +209,19 @@ def main(): except: print("Error:", fname) continue + change_made = remove_extra_Hs(st) or change_made + try: + change_made = meld_ace_nma(st) or change_made + except: + print("Error:", fname) + continue + change_made = reconnect_open_chains(st) or change_made if change_made: - new_fname = os.path.join(os.path.dirname(fname), '_'.join(os.path.basename(fname).split('_')[:-1])) - new_fname += f'_{st.formal_charge}.pdb' + new_fname = os.path.join( + os.path.dirname(fname), + "_".join(os.path.basename(fname).split("_")[:-1]), + ) + new_fname += f"_{st.formal_charge}.pdb" print(f"{fname} -> {new_fname}") st = build.reorder_protein_atoms_by_sequence(st) os.remove(fname) From 02ce480007b6f7bb88772b5b2085d6ec5ce9b3ca Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 17 Jul 2024 06:48:56 +0000 Subject: [PATCH 098/117] there are nitriles... --- biomolecules/pdb_pockets/cleanup.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index e568f9a..239019b 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -83,28 +83,28 @@ def meld_ace_nma(st): def reconnect_open_chains(st: Structure): broken_C = evaluate_asl( - st, "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2)" + st, "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l" ) broken_N = evaluate_asl( - st, "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2)" + st, "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l" ) change_made = False while broken_C: change_made = True - b_C = broken_C[0] + b_C = broken_C.pop() for b_N in broken_N: - if st.measure(b_C, b_N) < 1.5: + if st.measure(b_C, b_N) < 1.5 and not st.areBound(b_C, b_N): st.addBond(b_C, b_N, 1) st.atom[b_C].formal_charge = 0 st.atom[b_N].formal_charge = 0 merge_chain_names(st, st.atom[b_C], st.atom[b_N]) broken_C = evaluate_asl( st, - "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2)", + "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l", ) broken_N = evaluate_asl( st, - "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2)", + "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l", ) break return change_made @@ -188,12 +188,14 @@ def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--output_path", default=".") parser.add_argument("--prefix", default="") + parser.add_argument("--batch", type=int) return parser.parse_args() def main(): args = parse_args() file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) + file_list = file_list[10000*args.batch:10000*(args.batch+1)] for fname in tqdm(file_list): if not os.path.exists(fname): continue From bd6aa7d50fb0a6e15deb212b4ca241f4528b9b6a Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 18 Jul 2024 20:33:17 +0000 Subject: [PATCH 099/117] threshold was a little too tight --- biomolecules/pdb_pockets/combine_pockets.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/combine_pockets.py b/biomolecules/pdb_pockets/combine_pockets.py index 4c358d7..85f9a2d 100644 --- a/biomolecules/pdb_pockets/combine_pockets.py +++ b/biomolecules/pdb_pockets/combine_pockets.py @@ -142,7 +142,7 @@ def merge_structures( combined_st.addBond(lig_at, chain_at.index + offset, order) # Resolve any coordinating atoms in favor of a receptor atom - close_atoms = measure.get_close_atoms(combined_st, dist=0.01) + close_atoms = measure.get_close_atoms(combined_st, dist=0.05) ats_to_delete = [] for at1, at2 in close_atoms: if combined_st.atom[at2].chain == "c": From 44a56ea208234f7eace81615ef8008ef3dacbbb3 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 18 Jul 2024 20:33:53 +0000 Subject: [PATCH 100/117] also remove totally overlapping atoms (this may be addressed by changes to combine pockets) --- biomolecules/pdb_pockets/cleanup.py | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 239019b..8d4b39e 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -40,6 +40,12 @@ def merge_chain_names(st, at1, at2): if at.chain == old_chain: at.chain = main_chain +def remove_total_overlaps(st): + ats_to_delete = [max(at1, at2) for at1, at2 in measure.get_close_atoms(st, dist=0.05)] + if ats_to_delete: + st.deleteAtoms(ats_to_delete) + return True + return False def meld_ace_nma(st): change_made = False @@ -188,14 +194,15 @@ def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--output_path", default=".") parser.add_argument("--prefix", default="") - parser.add_argument("--batch", type=int) + parser.add_argument("--batch", type=int, default=0) return parser.parse_args() def main(): args = parse_args() - file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) - file_list = file_list[10000*args.batch:10000*(args.batch+1)] + #file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) + #file_list = file_list[10000*args.batch:10000*(args.batch+1)] + file_list = for fname in tqdm(file_list): if not os.path.exists(fname): continue @@ -218,6 +225,7 @@ def main(): print("Error:", fname) continue change_made = reconnect_open_chains(st) or change_made + change_made = remove_total_overlaps(st) or change_made if change_made: new_fname = os.path.join( os.path.dirname(fname), From 9bcc118e2cbf94fd5262cc0b0391c0443262c330 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Thu, 18 Jul 2024 22:42:12 +0000 Subject: [PATCH 101/117] oops --- biomolecules/pdb_pockets/cleanup.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 8d4b39e..c2df73c 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -200,9 +200,8 @@ def parse_args(): def main(): args = parse_args() - #file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) - #file_list = file_list[10000*args.batch:10000*(args.batch+1)] - file_list = + file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) + file_list = file_list[10000*args.batch:10000*(args.batch+1)] for fname in tqdm(file_list): if not os.path.exists(fname): continue From 53e4901eaa4cc07f908fd51c76391efb0df2151a Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 07:19:03 +0000 Subject: [PATCH 102/117] deprotonate carboxylic acids always --- biomolecules/pdb_pockets/biolip_extraction.py | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 5a4f466..078a68a 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -440,6 +440,28 @@ def run_prepwizard(fname: str, outname: str, fill_sidechain: bool) -> None: ) +def deprotonate_carboxylic_acids(st: Structure) -> bool: + """ + At physiological pH, it's a good assumption that any carboxylic acids + will be deprotonated. In the absence pKa's for ligands, we will make + this assumption. + + :param st: Structure with carboxylic acid groups that can be deprotonated + :return: True if structure needed to be deprotonated + """ + cooh_smarts = "[C](=[O])([O][H])" + try: + matched_ats = evaluate_smarts(st, cooh_smarts) + except ValueError: + matched_ats = [] + H_ats = {ats[-1] for ats in matched_ats} + O_ats = {ats[-2] for ats in matched_ats} + for O_at in O_ats: + st.atom[O_at].formal_charge -= 1 + st.deleteAtoms(H_ats) + return bool(H_ats) + + def deprotonate_phosphate_esters(st: Structure) -> bool: """ At physiological pH, it's a good assumption that any phosphate esters From bef0a7ebaf90b1d4a3ccf6ec381c95d62343b081 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 07:20:09 +0000 Subject: [PATCH 103/117] add more cleanup steps that probably aren't needed --- biomolecules/pdb_pockets/cleanup.py | 70 ++++++++++++++++++++++------- 1 file changed, 54 insertions(+), 16 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index c2df73c..4e9ecc1 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -4,7 +4,8 @@ from schrodinger.structure import Structure, StructureReader from schrodinger.structutils import build, measure -from schrodinger.structutils.analyze import evaluate_asl +from schrodinger.structutils.analyze import evaluate_asl, evaluate_smarts +from schrodinger.application.jaguar.utils import mmjag_update_lewis from tqdm import tqdm @@ -25,6 +26,51 @@ def remove_extra_Hs(st: Structure) -> bool: return False +def deprotonate_metal_bound_n(st): + N_to_dep = evaluate_asl(st, "atom.ele N and atom.att 4 and (withinbonds 1 metals) and (withinbonds 1 atom.ele H)") + ats_to_del = [] + for at_N in N_to_dep: + att_H = next(b_at for b_at in st.atom[at_N].bonded_atoms if b_at.atomic_number == 1) + ats_to_del.append(att_H) + st.atom[at_N].formal_charge = -1 + st.deleteAtoms(ats_to_del) + return bool(N_to_dep) + +def fix_heme_charge(st): + change_made=False + for res in st.chain['l'].residue: + if res.pdbres.strip() in {'HEM', 'HEC'}: + coord_n = [res.getAtomByPdbName(f' N{i} ') for i in "ABCD"] + if any(at is None for at in coord_n): + continue + if sum(at.formal_charge for at in coord_n) != -2: + for i, at in enumerate(coord_n, 1): + at.formal_charge = -1 * (i%2) + change_made = True + return change_made + +def fix_quartenary_N_charge(st): + quart_N = evaluate_smarts(st, '[NX4+0]') + for at_N in quart_N: + if all(bond.order == 1 for bond in st.atom[at_N[0]].bond): + st.atom[at_N[0]].formal_charge = 1 + return bool(quart_N) + +def non_physical_estate(st): + change_made = False + if (sum(at.atomic_number for at in st.atom) - st.formal_charge) % 2 != 0: + ats_before = st.atom_total + build.add_hydrogens(st) + if ats_before != st.atom_total: + change_made = True + else: + mmjag_update_lewis(st) + ats_before = st.atom_total + build.add_hydrogens(st) + if ats_before != st.atom_total: + change_made = True + return change_made + def merge_chain_names(st, at1, at2): chains = [at1.chain, at2.chain] if len(set(chains)) != 1: @@ -207,24 +253,16 @@ def main(): continue st = StructureReader.read(fname) change_made = fix_disrupted_disulfides(st) - try: - change_made = remove_ligand_ace_cap(st) or change_made - except: - print("Error:", fname) - continue - try: - change_made = remove_ligand_nma_cap(st) or change_made - except: - print("Error:", fname) - continue + change_made = remove_ligand_ace_cap(st) or change_made + change_made = remove_ligand_nma_cap(st) or change_made change_made = remove_extra_Hs(st) or change_made - try: - change_made = meld_ace_nma(st) or change_made - except: - print("Error:", fname) - continue + change_made = meld_ace_nma(st) or change_made change_made = reconnect_open_chains(st) or change_made change_made = remove_total_overlaps(st) or change_made + change_made = fix_quartenary_N_charge(st) or change_made + change_made = deprotonate_metal_bound_n(st) or change_made + change_made = fix_heme_charge(st) or change_made + change_made = non_physical_estate(st) or change_made if change_made: new_fname = os.path.join( os.path.dirname(fname), From d19e4a71bbdcd0a7749f654fabc48ef7c7a3f166 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 16:42:28 +0000 Subject: [PATCH 104/117] partition off nuclear option in cleanup.py --- biomolecules/pdb_pockets/cleanup.py | 51 +++++++++++++++++++---------- 1 file changed, 34 insertions(+), 17 deletions(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index 4e9ecc1..fe0eaec 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -2,10 +2,10 @@ import glob import os +from schrodinger.application.jaguar.utils import mmjag_update_lewis from schrodinger.structure import Structure, StructureReader from schrodinger.structutils import build, measure from schrodinger.structutils.analyze import evaluate_asl, evaluate_smarts -from schrodinger.application.jaguar.utils import mmjag_update_lewis from tqdm import tqdm @@ -27,35 +27,43 @@ def remove_extra_Hs(st: Structure) -> bool: def deprotonate_metal_bound_n(st): - N_to_dep = evaluate_asl(st, "atom.ele N and atom.att 4 and (withinbonds 1 metals) and (withinbonds 1 atom.ele H)") + N_to_dep = evaluate_asl( + st, + "atom.ele N and atom.att 4 and (withinbonds 1 metals) and (withinbonds 1 atom.ele H)", + ) ats_to_del = [] for at_N in N_to_dep: - att_H = next(b_at for b_at in st.atom[at_N].bonded_atoms if b_at.atomic_number == 1) + att_H = next( + b_at for b_at in st.atom[at_N].bonded_atoms if b_at.atomic_number == 1 + ) ats_to_del.append(att_H) st.atom[at_N].formal_charge = -1 st.deleteAtoms(ats_to_del) return bool(N_to_dep) + def fix_heme_charge(st): - change_made=False - for res in st.chain['l'].residue: - if res.pdbres.strip() in {'HEM', 'HEC'}: - coord_n = [res.getAtomByPdbName(f' N{i} ') for i in "ABCD"] + change_made = False + for res in st.chain["l"].residue: + if res.pdbres.strip() in {"HEM", "HEC"}: + coord_n = [res.getAtomByPdbName(f" N{i} ") for i in "ABCD"] if any(at is None for at in coord_n): continue if sum(at.formal_charge for at in coord_n) != -2: for i, at in enumerate(coord_n, 1): - at.formal_charge = -1 * (i%2) + at.formal_charge = -1 * (i % 2) change_made = True return change_made + def fix_quartenary_N_charge(st): - quart_N = evaluate_smarts(st, '[NX4+0]') + quart_N = evaluate_smarts(st, "[NX4+0]") for at_N in quart_N: if all(bond.order == 1 for bond in st.atom[at_N[0]].bond): st.atom[at_N[0]].formal_charge = 1 return bool(quart_N) + def non_physical_estate(st): change_made = False if (sum(at.atomic_number for at in st.atom) - st.formal_charge) % 2 != 0: @@ -71,6 +79,7 @@ def non_physical_estate(st): change_made = True return change_made + def merge_chain_names(st, at1, at2): chains = [at1.chain, at2.chain] if len(set(chains)) != 1: @@ -86,13 +95,17 @@ def merge_chain_names(st, at1, at2): if at.chain == old_chain: at.chain = main_chain + def remove_total_overlaps(st): - ats_to_delete = [max(at1, at2) for at1, at2 in measure.get_close_atoms(st, dist=0.05)] + ats_to_delete = [ + max(at1, at2) for at1, at2 in measure.get_close_atoms(st, dist=0.05) + ] if ats_to_delete: st.deleteAtoms(ats_to_delete) return True return False + def meld_ace_nma(st): change_made = False at_pairs = measure.get_close_atoms(st, dist=0.5) @@ -135,10 +148,12 @@ def meld_ace_nma(st): def reconnect_open_chains(st: Structure): broken_C = evaluate_asl( - st, "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l" + st, + "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l", ) broken_N = evaluate_asl( - st, "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l" + st, + "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l", ) change_made = False while broken_C: @@ -240,14 +255,15 @@ def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--output_path", default=".") parser.add_argument("--prefix", default="") - parser.add_argument("--batch", type=int, default=0) + parser.add_argument("--batch", type=int, default=0) + parser.add_argument("--nuclear_option", action="store_true") return parser.parse_args() def main(): args = parse_args() file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) - file_list = file_list[10000*args.batch:10000*(args.batch+1)] + file_list = file_list[10000 * args.batch : 10000 * (args.batch + 1)] for fname in tqdm(file_list): if not os.path.exists(fname): continue @@ -260,9 +276,10 @@ def main(): change_made = reconnect_open_chains(st) or change_made change_made = remove_total_overlaps(st) or change_made change_made = fix_quartenary_N_charge(st) or change_made - change_made = deprotonate_metal_bound_n(st) or change_made - change_made = fix_heme_charge(st) or change_made - change_made = non_physical_estate(st) or change_made + if args.nuclear_option: + change_made = deprotonate_metal_bound_n(st) or change_made + change_made = fix_heme_charge(st) or change_made + change_made = non_physical_estate(st) or change_made if change_made: new_fname = os.path.join( os.path.dirname(fname), From 60f627ee63fd4ae4c292094ba6ebd27fbc149740 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 17:11:05 +0000 Subject: [PATCH 105/117] don't try and redownload if we already have it --- biomolecules/pdb_pockets/biolip_extraction.py | 38 ++++++++++--------- 1 file changed, 21 insertions(+), 17 deletions(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index 078a68a..e41226e 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -1,7 +1,6 @@ import argparse import glob import os -import random import shutil import subprocess import sys @@ -11,7 +10,7 @@ import pandas as pd from schrodinger.adapter import evaluate_smarts from schrodinger.protein.captermini import CapTermini -from schrodinger.structure import Structure, StructureReader, StructureWriter +from schrodinger.structure import Structure, StructureReader from schrodinger.structutils import analyze, build SCHRO = "/private/home/levineds/schrodinger2024-2" @@ -279,8 +278,9 @@ def retreive_ligand_and_env( # Cleanup the remaining prepped files for this pdb_id print("done with", pdb_count, pdb_id) - for fname in prepped_pdb_fnames: - os.remove(fname) + for fname in prepped_pdb_fnames + [f'{pdb_id}.pdb', f'{pdb_id}.cif']: + if os.path.exists(fname): + os.remove(fname) def download_cif(pdb_id: str) -> Structure: @@ -294,25 +294,26 @@ def download_cif(pdb_id: str) -> Structure: # Try for the PDB fname = f"{pdb_id}.pdb" - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) + if not os.path.exists(fname): + subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) if os.path.exists(fname): st = next(StructureReader(fname), None) - os.remove(fname) if st is not None: return st # Failing that, take the CIF fname = f"{pdb_id}.cif" - for i in range(3): - subprocess.run( - [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] - ) - if os.path.exists(fname): - break + if not os.path.exists(fname): + for i in range(3): + subprocess.run( + [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] + ) + if os.path.exists(fname): + break + else: + time.sleep(10) else: - time.sleep(10) - else: - raise ConnectionError + raise ConnectionError st = next(StructureReader(fname), None) if st is None: @@ -341,7 +342,6 @@ def get_prepped_protein( """ chains = {row["receptor_chain"], row["ligand_chain"]} outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" - fname = f"{pdb_id}.cif" maename = f"{pdb_id}.maegz" if not prep: @@ -388,10 +388,14 @@ def get_prepped_protein( print( f'{pdb_id}, {row["receptor_chain"]}{row["binding_site_number_code"]} needed phosphate deprotonation' ) + if deprotonate_carboxylic_acids(st): + print( + f'{pdb_id}, {row["receptor_chain"]}{row["binding_site_number_code"]} needed carboxylic acid deprotonation' + ) st = build.reorder_protein_atoms_by_sequence(st) # Cleanup - for file_to_del in (maename, fname): + for file_to_del in (maename,): if os.path.exists(file_to_del): os.remove(file_to_del) for deldir in glob.glob(f"{pdb_id}-???"): From 47d92951ba38adc826bdca5e0286b4fab12a232e Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 22:28:56 +0000 Subject: [PATCH 106/117] oops --- biomolecules/pdb_pockets/biolip_extraction.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py index e41226e..bbca560 100644 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ b/biomolecules/pdb_pockets/biolip_extraction.py @@ -278,7 +278,7 @@ def retreive_ligand_and_env( # Cleanup the remaining prepped files for this pdb_id print("done with", pdb_count, pdb_id) - for fname in prepped_pdb_fnames + [f'{pdb_id}.pdb', f'{pdb_id}.cif']: + for fname in prepped_pdb_fnames.union([f'{pdb_id}.pdb', f'{pdb_id}.cif']): if os.path.exists(fname): os.remove(fname) From 514ea62602197b0d50a30a337694a6494f674129 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 22:29:17 +0000 Subject: [PATCH 107/117] make sure COOH is deprotonated --- biomolecules/pdb_pockets/cleanup.py | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index fe0eaec..b8fd951 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -42,6 +42,28 @@ def deprotonate_metal_bound_n(st): return bool(N_to_dep) +def deprotonate_carboxylic_acids(st: Structure) -> bool: + """ + At physiological pH, it's a good assumption that any carboxylic acids + will be deprotonated. In the absence pKa's for ligands, we will make + this assumption. + + :param st: Structure with carboxylic acid groups that can be deprotonated + :return: True if structure needed to be deprotonated + """ + cooh_smarts = "[C](=[O])([O][H])" + try: + matched_ats = evaluate_smarts(st, cooh_smarts) + except ValueError: + matched_ats = [] + H_ats = {ats[-1] for ats in matched_ats} + O_ats = {ats[-2] for ats in matched_ats} + for O_at in O_ats: + st.atom[O_at].formal_charge -= 1 + st.deleteAtoms(H_ats) + return bool(H_ats) + + def fix_heme_charge(st): change_made = False for res in st.chain["l"].residue: @@ -269,6 +291,7 @@ def main(): continue st = StructureReader.read(fname) change_made = fix_disrupted_disulfides(st) + change_made = deprotonate_carboxylic_acids(st) or change_made change_made = remove_ligand_ace_cap(st) or change_made change_made = remove_ligand_nma_cap(st) or change_made change_made = remove_extra_Hs(st) or change_made From 7b1d14ada64c349101caf45c7b3fad2ac13c671e Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 19 Jul 2024 22:56:03 +0000 Subject: [PATCH 108/117] add files for running MD with Desmond --- biomolecules/pdb_pockets/desmond_md.cfg | 91 +++++++++++++++++++++ biomolecules/pdb_pockets/desmond_md.msj | 100 ++++++++++++++++++++++++ biomolecules/pdb_pockets/run_md.py | 18 +++++ 3 files changed, 209 insertions(+) create mode 100644 biomolecules/pdb_pockets/desmond_md.cfg create mode 100644 biomolecules/pdb_pockets/desmond_md.msj create mode 100644 biomolecules/pdb_pockets/run_md.py diff --git a/biomolecules/pdb_pockets/desmond_md.cfg b/biomolecules/pdb_pockets/desmond_md.cfg new file mode 100644 index 0000000..35b9966 --- /dev/null +++ b/biomolecules/pdb_pockets/desmond_md.cfg @@ -0,0 +1,91 @@ +annealing = false +backend = { +} +bigger_rclone = false +box = ? +checkpt = { + first = 0.0 + interval = 240.06 + name = "$JOBNAME.cpt" + write_last_step = true +} +cpu = 1 +cutoff_radius = 9.0 +dipole_moment = false +ebias_force = false +elapsed_time = 0.0 +energy_group = false +eneseq = { + first = 0.0 + interval = 1.2 + name = "$JOBNAME$[_replica$REPLICA$].ene" +} +ensemble = { + barostat = { + tau = 2.0 + } + class = NVT + method = Langevin + thermostat = { + tau = 1.0 + } +} +gaussian_force = false +glue = solute +lambda_dynamics = false +maeff_output = { + center_atoms = solute + first = 0.0 + interval = 120.0 + name = "$JOBNAME$[_replica$REPLICA$]-out.cms" + periodicfix = true + trjdir = "$JOBNAME$[_replica$REPLICA$]_trj" +} +meta = false +meta_file = ? +msd = false +pressure = 1.01325 +pressure_tensor = false +randomize_velocity = { + first = 0.0 + interval = inf + seed = 2007 + temperature = "@*.temperature" +} +restraints = { + existing = ignore + new = [ + { + name = posre_harm + atoms = ["atom.pt CA or (res ACE and atom.pt CH3)"] + force_constants = [100 100 100] + } + ] +} +rnemd = false +simbox = { + first = 0.0 + interval = 1.2 + name = "$JOBNAME$[_replica$REPLICA$]_simbox.dat" +} +spatial_temperature = false +surface_tension = 0.0 +taper = false +temperature = [ + [300.0 0 ] +] +time = 1020.0 +timestep = [0.002 0.002 0.006 ] +trajectory = { + center = [] + first = 0.0 + format = dtr + frames_per_file = 250 + interval = 10.0 + name = "$JOBNAME$[_replica$REPLICA$]_trj" + periodicfix = true + write_last_vel = false + write_velocity = false +} +wall_force = false + diff --git a/biomolecules/pdb_pockets/desmond_md.msj b/biomolecules/pdb_pockets/desmond_md.msj new file mode 100644 index 0000000..55d221f --- /dev/null +++ b/biomolecules/pdb_pockets/desmond_md.msj @@ -0,0 +1,100 @@ +# Desmond standard NVT relaxation protocol +# All times are in the unit of ps. +# Energy is in the unit of kcal/mol. +task { + task = "desmond:auto" + set_family = { + desmond = { + checkpt.write_last_step = no + } + } +} + +build_geometry { + box = { + shape = orthorhombic + size = [50.0 50.0 50.0 ] + size_type = buffer + } + neutralize_system = false + override_forcefield = OPLS_2005 + rezero_system = false + solvate_system = false +} + +assign_forcefield { + forcefield = OPLS_2005 +} + +simulate { + title = "Brownian Dynamics NVT, T = 10 K, small timesteps, and restraints on solute heavy atoms, 100ps" + annealing = off + time = 100 + timestep = [0.001 0.001 0.003 ] + temperature = 10.0 + ensemble = { + class = "NVT" + method = "Brownie" + brownie = { + delta_max = 0.1 + } + } + restraints.new = [{ + name = posre_harm + atoms = solute_heavy_atom + force_constants = 50.0 + }] +} + + +simulate { + title = "NVT, T = 10 K, small timesteps, and restraints on solute heavy atoms, 12ps" + annealing = off + time = 12 + timestep = [0.001 0.001 0.003] + temperature = 10.0 + restraints.new = [{ + name = posre_harm + atoms = solute_heavy_atom + force_constants = 50.0 + }] + ensemble = { + class = NVT + method = Langevin + thermostat.tau = 0.1 + } + + randomize_velocity.interval = 1.0 + eneseq.interval = 0.3 + trajectory.center = solute +} + +simulate { + title = "Minimization, 100ps" + annealing = off + time = 100 + timestep = [0.001 0.001 0.003 ] + temperature = 10.0 + ensemble = { + class = "NVT" + method = "Brownie" + brownie = { + delta_max = 0.1 + } + thermostat = { + tau = 1.0 + } + } + restrain = none + restraints = { + existing = ignore + new = [] + } +} +simulate { + cfg_file = "desmond_md_job_10.cfg" + jobname = "$MAINJOBNAME" + dir = "." + compress = "" +} + diff --git a/biomolecules/pdb_pockets/run_md.py b/biomolecules/pdb_pockets/run_md.py new file mode 100644 index 0000000..b97dd85 --- /dev/null +++ b/biomolecules/pdb_pockets/run_md.py @@ -0,0 +1,18 @@ +import argparse +import glob +import os + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument("--output_path", default=".") + return parser.parse_args() + + +def main(): + args = parse_args() + file_list = glob.glob(os.path.join(args.output_path, f"*.mae")) + with open('paths_list.txt', 'w') as fh: + fh.write('\n'.join(file_list)) + +if __name__ == "__main__": + main() From 07b391d5973c22ab50c8145e70c5931a7b754e9b Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Sat, 20 Jul 2024 04:36:43 +0000 Subject: [PATCH 109/117] use absolute path --- biomolecules/pdb_pockets/desmond_md.msj | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/desmond_md.msj b/biomolecules/pdb_pockets/desmond_md.msj index 55d221f..8508bdb 100644 --- a/biomolecules/pdb_pockets/desmond_md.msj +++ b/biomolecules/pdb_pockets/desmond_md.msj @@ -92,7 +92,7 @@ simulate { } } simulate { - cfg_file = "desmond_md_job_10.cfg" + cfg_file = "/private/home/levineds/om-data/biomolecules/pdb_pockets/desmond_md.cfg" jobname = "$MAINJOBNAME" dir = "." compress = "" From abf06076440ea545bd434fc7f24c720ec0786ae6 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Mon, 22 Jul 2024 06:19:58 +0000 Subject: [PATCH 110/117] ensure ligand chain is present --- biomolecules/pdb_pockets/cleanup.py | 23 ++++++++++++++++++++++- 1 file changed, 22 insertions(+), 1 deletion(-) diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py index b8fd951..73a2036 100644 --- a/biomolecules/pdb_pockets/cleanup.py +++ b/biomolecules/pdb_pockets/cleanup.py @@ -26,6 +26,26 @@ def remove_extra_Hs(st: Structure) -> bool: return False +def rename_coord_chain(st): + chain_names = [ch.name for ch in st.chain] + if "l" not in chain_names and "c" in chain_names: + lig = [] + if len(st.chain["c"].getAtomList()) == 1: + lig = st.chain["c"].getAtomList() + if not lig: + lig = evaluate_asl(st, "chain c and metals") + if not lig: + lig = evaluate_asl(st, "chain c and res D8U") + if not lig: + lig = evaluate_asl(st, "chain c and atom.ato >=18") + if not lig: + lig = evaluate_asl(st, "chain c and atom.ele F,Cl,Br,I") + for at in lig: + st.atom[at].chain = "l" + if lig: + return True + + def deprotonate_metal_bound_n(st): N_to_dep = evaluate_asl( st, @@ -290,7 +310,8 @@ def main(): if not os.path.exists(fname): continue st = StructureReader.read(fname) - change_made = fix_disrupted_disulfides(st) + change_made = rename_coord_chain(st) + change_made = fix_disrupted_disulfides(st) or change_made change_made = deprotonate_carboxylic_acids(st) or change_made change_made = remove_ligand_ace_cap(st) or change_made change_made = remove_ligand_nma_cap(st) or change_made From 61287283a5f299c71b19724cc0c9c7ea94fc61e8 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Fri, 26 Jul 2024 16:34:10 +0000 Subject: [PATCH 111/117] Use chain to identify solvent vs. solute --- electrolytes/solvation_shell_extract.py | 13 ++----------- electrolytes/solvation_shell_utils.py | 12 ++++-------- 2 files changed, 6 insertions(+), 19 deletions(-) diff --git a/electrolytes/solvation_shell_extract.py b/electrolytes/solvation_shell_extract.py index 0f1451e..5499fb0 100644 --- a/electrolytes/solvation_shell_extract.py +++ b/electrolytes/solvation_shell_extract.py @@ -74,8 +74,6 @@ def extract_solvation_shells( elif spec_type == "solvent": solvents[species] = res spec_dicts = {"solute": solutes, "solvent": solvents} - solute_resnames = set(solutes.values()) - solvent_resnames = set(solvents.values()) # Read structures structures = list(StructureReader(os.path.join(input_dir, "system_output.pdb"))) @@ -108,8 +106,6 @@ def extract_solvation_shells( radius, residue, spec_type, - solute_resnames, - solvent_resnames, shells_per_frame, max_shell_size, ) @@ -163,8 +159,6 @@ def extract_residue_from_structure( radius: float, residue: str, spec_type: str, - solute_resnames: list[str], - solvent_resnames: list[str], shells_per_frame: int, max_shell_size: int, ) -> Structure: @@ -176,8 +170,6 @@ def extract_residue_from_structure( (initially in the case of solutes) :param resiude: name of residue to consider :param spec_type: type of species being extracted, either 'solute' or 'solvent' - :param solute_resnames: list of names of solute residues - :param solvent_resnames: list of names of solvent residues :param shells_per_frame: number of shells to extract from this structure :param max_shell_size: maximum number of atoms in a shell :return: extracted shell structure @@ -198,7 +190,7 @@ def extract_residue_from_structure( if spec_type == "solvent": # Only keep the shells that have no solute atoms and below a maximum size - solute_atoms = analyze.evaluate_asl(st, f'res {",".join(solute_resnames)}') + solute_atoms = st.chain["A"].getAtomList() shells = [ (shell, central_mol) for shell, central_mol in zip(shells, central_mol_nums) @@ -216,7 +208,7 @@ def extract_residue_from_structure( expanded_shell_ats = shell_ats # If we have a solvent-free system, don't expand shells around solutes, # because we'll always have solutes and will never terminate - if solvent_resnames: + if "B" in {ch.name for ch in st.chain}: # TODO: how to choose the mean/scale for sampling? # Should the mean be set to the number of atoms in the non-expanded shell? upper_bound = max(len(shell_ats), generate_lognormal_samples()[0]) @@ -226,7 +218,6 @@ def extract_residue_from_structure( shell_ats, central_solute, radius, - solute_resnames, max_shell_size=upper_bound, ) expanded_shell = extract_contracted_shell( diff --git a/electrolytes/solvation_shell_utils.py b/electrolytes/solvation_shell_utils.py index dda6f2c..8076083 100644 --- a/electrolytes/solvation_shell_utils.py +++ b/electrolytes/solvation_shell_utils.py @@ -28,7 +28,6 @@ def expand_shell( shell_ats: Set[int], central_solute: int, radius: float, - solute_res_names: List[str], max_shell_size: int = 200, ) -> Set[int]: """ @@ -41,25 +40,24 @@ def expand_shell( shell_ats: Set of atom indices (of `st`) in a shell (1-indexed) central_solute: Molecule index (of 'st') of the central solute in the shell radius: Solvation radius (Angstroms) to consider - solute_res_names: List of residue names that correspond to solute atoms in the simulation max_shell_size: Maximum size (in atoms) of the expanded shell Returns: Set of atom indices (of `st`) of the expanded shell (1-indexed) """ solutes_included = set([central_solute]) - def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): + def get_new_solutes(st, shell_ats, solutes_included): new_solutes = set() for at in shell_ats: # If atom is part of a non-central solute molecule - should expand the shell if ( st.atom[at].molecule_number not in solutes_included - and st.atom[at].getResidue().pdbres.strip() in solute_res_names + and st.atom[at].chain == "A" ): new_solutes.add(st.atom[at].molecule_number) return new_solutes - new_solutes = get_new_solutes(st, shell_ats, solutes_included, solute_res_names) + new_solutes = get_new_solutes(st, shell_ats, solutes_included) while new_solutes: # add entire residues within solvation shell radius of any extra solute atoms new_shell_ats = shell_ats.union( @@ -71,9 +69,7 @@ def get_new_solutes(st, shell_ats, solutes_included, solute_res_names): if len(new_shell_ats) <= max_shell_size: shell_ats = new_shell_ats solutes_included.update(new_solutes) - new_solutes = get_new_solutes( - st, shell_ats, solutes_included, solute_res_names - ) + new_solutes = get_new_solutes(st, shell_ats, solutes_included) else: break From 65b9c0b74e3b463629ff25dc15e50b71152e656a Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Wed, 31 Jul 2024 19:10:05 +0000 Subject: [PATCH 112/117] Sample OOD solvation shells for 10% of inputs --- electrolytes/solvation/solvate.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/electrolytes/solvation/solvate.py b/electrolytes/solvation/solvate.py index ed6bfce..bf437a3 100644 --- a/electrolytes/solvation/solvate.py +++ b/electrolytes/solvation/solvate.py @@ -418,10 +418,8 @@ def dump_xyzs( # 3. Generate `n` random solvation shells with combinations of random combinations of components (ions, # neutral species, etc.) - # TODO: CHANGE THESE - # These numbers just for testing num_dimers = args.num_dimers - num_random_shells = 1 + num_random_shells = args.num_random_shells # Note: this is currently unused max_core_molecule_size = args.max_core_molecule_size max_atom_budget = args.max_atom_budget @@ -507,9 +505,9 @@ def dump_xyzs( ) # Out-of-distribution (OOD) data - # TODO: probably shouldn't have an OOD point for EVERY structure. - # Could do a random subsample - # Could actually do this procedure on a totally different set of molecules? + # We generate an OOD point for 10% of the input structures + if random.random() > 0.1: + continue ood_solvating_info = info_from_smiles( metals_ood + other_cations_ood + anions_ood + neutrals_ood @@ -561,4 +559,4 @@ def dump_xyzs( complexes=[ood_complex], prefix=subname, path=(ood_dir / subname), - ) \ No newline at end of file + ) From a477adae7564aa0655b030ef027166a73182b540 Mon Sep 17 00:00:00 2001 From: Daniel Levine Date: Tue, 13 Aug 2024 17:59:41 +0000 Subject: [PATCH 113/117] Revert "merge main" This reverts commit 2cc579340b08a317b194515c831eb4147960bca2, reversing changes made to 61287283a5f299c71b19724cc0c9c7ea94fc61e8. --- README.md | 1 - biomolecules/geom/sample_geom_drugs.py | 94 - .../geom/write_geom_drugs_structures.py | 89 - biomolecules/pdb_pockets/biolip_extraction.py | 668 -- biomolecules/pdb_pockets/cleanup.py | 340 - biomolecules/pdb_pockets/combine_pockets.py | 169 - biomolecules/pdb_pockets/desmond_md.cfg | 91 - biomolecules/pdb_pockets/desmond_md.msj | 100 - biomolecules/pdb_pockets/run_md.py | 18 - electrolytes/__init__.py | 0 electrolytes/functionalization/README.md | 32 - electrolytes/functionalization/__init__.py | 0 .../functional_group_substitution.ipynb | 7262 ----------------- .../functionalization/substitutions.py | 1088 --- electrolytes/solvation/README.md | 35 - electrolytes/solvation/__init__.py | 0 electrolytes/solvation/solvate.py | 562 -- metal-organics/README.md | 35 - metal-organics/analyze_outputs.py | 35 - metal-organics/architector_sampling.py | 272 - metal-organics/generate_structures.py | 54 - metal-organics/ligand_sample_dataframe.pkl | Bin 196841 -> 0 bytes metal-organics/metal_sample_dataframe.pkl | Bin 5024 -> 0 bytes metal-organics/mprun.py | 117 - metal-organics/slurm_launch.sh | 16 - omdata/electrolyte_utils.py | 74 - omdata/orca/basis/def2-tzvpd.bas | 5328 ------------ omdata/orca/calc.py | 186 +- omdata/orca/recipes.py | 108 +- setup.py | 5 +- 30 files changed, 37 insertions(+), 16742 deletions(-) delete mode 100644 biomolecules/geom/sample_geom_drugs.py delete mode 100644 biomolecules/geom/write_geom_drugs_structures.py delete mode 100644 biomolecules/pdb_pockets/biolip_extraction.py delete mode 100644 biomolecules/pdb_pockets/cleanup.py delete mode 100644 biomolecules/pdb_pockets/combine_pockets.py delete mode 100644 biomolecules/pdb_pockets/desmond_md.cfg delete mode 100644 biomolecules/pdb_pockets/desmond_md.msj delete mode 100644 biomolecules/pdb_pockets/run_md.py delete mode 100644 electrolytes/__init__.py delete mode 100644 electrolytes/functionalization/README.md delete mode 100644 electrolytes/functionalization/__init__.py delete mode 100644 electrolytes/functionalization/functional_group_substitution.ipynb delete mode 100644 electrolytes/functionalization/substitutions.py delete mode 100644 electrolytes/solvation/README.md delete mode 100644 electrolytes/solvation/__init__.py delete mode 100644 electrolytes/solvation/solvate.py delete mode 100644 metal-organics/analyze_outputs.py delete mode 100644 metal-organics/architector_sampling.py delete mode 100644 metal-organics/generate_structures.py delete mode 100644 metal-organics/ligand_sample_dataframe.pkl delete mode 100644 metal-organics/metal_sample_dataframe.pkl delete mode 100644 metal-organics/mprun.py delete mode 100644 metal-organics/slurm_launch.sh delete mode 100644 omdata/electrolyte_utils.py delete mode 100644 omdata/orca/basis/def2-tzvpd.bas diff --git a/README.md b/README.md index 8b13789..e69de29 100644 --- a/README.md +++ b/README.md @@ -1 +0,0 @@ - diff --git a/biomolecules/geom/sample_geom_drugs.py b/biomolecules/geom/sample_geom_drugs.py deleted file mode 100644 index 37e651b..0000000 --- a/biomolecules/geom/sample_geom_drugs.py +++ /dev/null @@ -1,94 +0,0 @@ -import os -import json -import pickle -import random -import argparse -import tqdm - - -def write_pickle(data, path): - with open(path, "wb") as f: - pickle.dump(data, f, pickle.HIGHEST_PROTOCOL) - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--base_path", - type=str, - required=True, - help="Path to where you untarred the rdkit folder i.e. path/to/rdkit_folder", - ) - parser.add_argument( - "--out_path", type=str, required=True, help="Path to the output directory" - ) - - return parser.parse_args() - - -def main(): - - args = parse_args() - - # rdkit folder downloaded 2024-03-01 - base_path = args.base_path - out_path = args.out_path - drugs_file = os.path.join(base_path, "summary_drugs.json") - - with open(drugs_file, "r") as f: - drugs_summ = json.load(f) - - # set random seed - random.seed(42) - - train_id_list = [] - val_id_list = [] - id_mol_dict = {} - missing_drugs = [] - - for drug in tqdm.tqdm(drugs_summ.keys()): - # not all drugs have necessary keys - try: - charge = drugs_summ[drug]["charge"] - pickle_path = drugs_summ[drug]["pickle_path"] - except KeyError: - missing_drugs.append(drug) - continue - pp = os.path.join(base_path, pickle_path) - with open(pp, "rb") as f: - mol_dict = pickle.load(f) - rand = random.random() - # generate train ids with 85% probability - ~5% charged - # sampling happens at the molecule level - if charge == 0 and rand > 0.15: - for i, c in enumerate(mol_dict["conformers"]): - train_id_list.append(c["geom_id"]) - id_mol_dict[c["geom_id"]] = { - "pickle_path": drugs_summ[drug]["pickle_path"], - "conf_idx": i, - "charge": charge, - "molecule": drug, - } - # if charge != 0 or rand =< 0.15: - else: - for i, c in enumerate(mol_dict["conformers"]): - val_id_list.append(c["geom_id"]) - id_mol_dict[c["geom_id"]] = { - "pickle_path": drugs_summ[drug]["pickle_path"], - "conf_idx": i, - "charge": charge, - "molecule": drug, - } - # shuffle train list - for i in range(3): - random.shuffle(train_id_list) - - # write out train/val ids, id_mol_dict, and missing drugs - write_pickle(train_id_list, os.path.join(out_path, "train_ids.pkl")) - write_pickle(val_id_list, os.path.join(out_path, "val_ids.pkl")) - write_pickle(id_mol_dict, os.path.join(out_path, "id_mol_dict.pkl")) - write_pickle(missing_drugs, os.path.join(out_path, "missing_drugs.pkl")) - - -if __name__ == "__main__": - main() diff --git a/biomolecules/geom/write_geom_drugs_structures.py b/biomolecules/geom/write_geom_drugs_structures.py deleted file mode 100644 index 79866b3..0000000 --- a/biomolecules/geom/write_geom_drugs_structures.py +++ /dev/null @@ -1,89 +0,0 @@ -import os -import pickle -import argparse -import tqdm - -from rdkit.Chem.rdmolfiles import MolToXYZFile - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument( - "--base_path", - type=str, - required=True, - help="Path to where you untarred the rdkit folder id.e. path/to/rdkit_folder", - ) - parser.add_argument( - "--parent_path", - type=str, - required=True, - help="Path to the parent directory where structures will be written", - ) - parser.add_argument( - "--geom_ids_path", - type=str, - required=True, - help="Path to geom ids pkl to write structures for", - ) - parser.add_argument( - "--idmol_path", - type=str, - required=True, - help="Path to id_mol_dict.pkl", - ) - parser.add_argument( - "--start_idx", - type=int, - required=True, - help="Index in split ids to start writting files", - ) - parser.add_argument( - "--stop_idx", - type=int, - required=True, - help="Index in split ids to stop writting files", - ) - - return parser.parse_args() - - -def main(): - - args = parse_args() - - # rdkit folder downloaded 2024-03-01 - base_path = args.base_path - parent_path = args.parent_path - geom_ids_path = args.geom_ids_path - idmol_path = args.idmol_path - start_idx = args.start_idx - stop_idx = args.stop_idx - - # read split ids - with open(geom_ids_path, "rb") as f: - geom_ids = pickle.load(f) - - with open(idmol_path, "rb") as f: - idmol = pickle.load(f) - - outdir = os.path.join(parent_path, f"{start_idx}_{stop_idx}_geom_structures") - assert not os.path.exists(outdir), f"Directory {outdir} already exists" - os.makedirs(outdir) - - for id in tqdm.tqdm(geom_ids[start_idx:stop_idx]): - pp = os.path.join(base_path, idmol[id]["pickle_path"]) - with open(pp, "rb") as f: - mol_dict = pickle.load(f) - # get charge, multiplicity, and conformer index - charge = idmol[id]["charge"] - # defaults to 1 if not explicitly set - multiplicity = idmol[id].get("multiplicity", 1) - conf_idx = idmol[id]["conf_idx"] - f_name = os.path.join(outdir, f"{id}_{charge}_{multiplicity}.xyz") - # write xyz file - MolToXYZFile(mol_dict["conformers"][conf_idx]["rd_mol"], f_name) - - -if __name__ == "__main__": - main() diff --git a/biomolecules/pdb_pockets/biolip_extraction.py b/biomolecules/pdb_pockets/biolip_extraction.py deleted file mode 100644 index bbca560..0000000 --- a/biomolecules/pdb_pockets/biolip_extraction.py +++ /dev/null @@ -1,668 +0,0 @@ -import argparse -import glob -import os -import shutil -import subprocess -import sys -import time -from typing import List, Tuple - -import pandas as pd -from schrodinger.adapter import evaluate_smarts -from schrodinger.protein.captermini import CapTermini -from schrodinger.structure import Structure, StructureReader -from schrodinger.structutils import analyze, build - -SCHRO = "/private/home/levineds/schrodinger2024-2" - - -class MissingAtomsError(Exception): - pass - - -class MissingResiduesError(Exception): - pass - - -class MutateError(Exception): - pass - - -def get_biolip_db(lig_type: str = "reg", pklpath: str = ".") -> pd.DataFrame: - pkl_name = os.path.join(pklpath, "biolip_df.pkl") - if os.path.exists(pkl_name): - biolip_df = pd.read_pickle(pkl_name) - else: - columns = [ - "pdb_id", - "receptor_chain", - "resolution", - "binding_site_number_code", - "ligand_id", - "ligand_chain", - "ligand_serial_number", - "binding_site_residues_pdb", - "binding_site_residues_re-numbered", - "catalytic_site_residues_pdb", - "catalytic_site_residues_re-numbered", - "ec_number", - "go_terms", - "binding_affinity_manual", - "binding_affinity_binding_moad", - "binding_affinity_pdbbind_cn", - "binding_affinity_bindingdb", - "uniprot_ids", - "pubmed_id", - "ligand_residue_number", - "receptor_sequence", - ] - types = {col: str for col in columns} - types["ligand_serial_number"] = int - biolip_df = pd.read_csv( - "BioLiP_05_31_2024.txt", - sep="\t", - names=columns, - dtype=types, - keep_default_na=False, - ) - # Parse the ligand specification - biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ - "ligand_residue_number" - ].str.split("~", expand=True) - biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].fillna( - biolip_df["ligand_residue_number"] - ) - biolip_df[["ligand_residue_number", "ligand_residue_inscode"]] = biolip_df[ - "ligand_residue_number" - ].str.extract(r"(-?\d+)([A-Z\s]+)$") - biolip_df["ligand_residue_end"] = biolip_df["ligand_residue_end"].str.extract( - r"(-?\d+)" - ) - biolip_df[["ligand_residue_number", "ligand_residue_end"]] = biolip_df[ - ["ligand_residue_number", "ligand_residue_end"] - ].astype(int) - - # Remove duplicate pockets: These are pockets with the same ligand binding - # to exactly the same residues (including numbering). We don't require the - # PDB IDs to also match as closely related proteins or structures may have - # conserved binding sites which are still duplicates of each other. - biolip_df.drop_duplicates( - subset=["ligand_id", "binding_site_residues_pdb"], inplace=True - ) - # Remove duplicate pockets: These are pockets with the same ligand in - # the same structure, often on different copies of the same chain. Sometimes - # there are residues that are right at the edge of inclusion, and so the - # pockets may be "different" by inclusion of an additional, marginal residue. - # We opt for only the smallest of such binding sites since these indicate the - # key interactions. - biolip_df = ( - biolip_df.groupby(["pdb_id", "ligand_id"], group_keys=False)[ - biolip_df.columns - ] - .apply(get_minimal_pockets) - .sort_index() - ) - - # Note whether this molecule is drug-like by checking if it has any - # binding informations - biolip_df["has_binding_info"] = ( - biolip_df[ - [ - "binding_affinity_manual", - "binding_affinity_binding_moad", - "binding_affinity_pdbbind_cn", - "binding_affinity_bindingdb", - ] - ] - != "" - ).any(axis=1) - biolip_df.to_pickle(pkl_name) - - if lig_type == "macromol": - biolip_df = biolip_df[biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] - elif lig_type == "reg": - biolip_df = biolip_df[~biolip_df["ligand_id"].isin(["dna", "rna", "peptide"])] - return biolip_df - - -def is_sublist(smaller: List, larger: List) -> bool: - """ - Determine if the smaller list is a (not necessarily contiguous) - sub-list of the larger list - - :param smaller: smaller list - :param larger: larger list - :return: True if smaller is ordered sublist of larger - """ - it = iter(larger) - return all(item in it for item in smaller) - - -def get_minimal_pockets(group: pd.DataFrame) -> List[int]: - """ - Filter BioLiP entries by selecting the smallest set of residues that - bind a particular ligand in a particular protein. - - :param group: entries which share a pdb_id and ligand_id to filter - :return: locations of entries in the group which are minimal binding pockets - """ - group["residue_list"] = group["binding_site_residues_pdb"].apply( - lambda x: x.split() - ) - subset_rows = [] - rows = [row for _, row in group.iterrows()] - rows.sort(key=lambda x: len(x["residue_list"])) - while len(rows) > 1: - subset_rows.append(rows[0]) - rows = [ - row - for row in rows[1:] - if not is_sublist(rows[0]["residue_list"], row["residue_list"]) - ] - subset_rows.extend(rows) - group.drop(columns=["residue_list"], inplace=True) - return group.loc[[row.name for row in subset_rows]] - - -def certain_rows(df): - rows = [ - ("6qs4", "D", "BS03"), - ] # ('6qs4', 'D', 'BS02')] - rows_df = pd.DataFrame( - rows, columns=["pdb_id", "receptor_chain", "binding_site_number_code"] - ) - filtered = pd.merge( - df, - rows_df, - how="inner", - on=["pdb_id", "receptor_chain", "binding_site_number_code"], - ) - return filtered - - -def retreive_ligand_and_env( - biolip_df: pd.DataFrame, - ligand_size_limit: int = 250, - start_pdb: int = 0, - end_pdb: int = 1000, - output_path: str = ".", - fill_sidechain: bool = True, -) -> None: - """ - Extract ligand and its environment from BioLiP examples - - Procedure is as follows, for each protein in BioLiP: - 1) Download the structure and prepare it with PrepWizard (re-using already prepared proteins if possible) - 2) Obtain list of atoms which are assigned as ligands or receptors in BioLiP - 3) Extract the receptor residues and cap them to match the source protein - 4) Write the extracted structure to a pdb file - - :param biolip_df: Dataframe storing BioLiP database - :param ligand_size_limit: largest ligand size to extract from BioLiP - :param start_pdb: index of first pdb to run in the dataframe - :param end_pdb: index of last pdb to run in dataframe - :param output_path: where to store results - :param fill_sidechain: If True, PrepWizard will try and fill in missing side chains - """ - # random.seed(12341) - # biolip_df = certain_rows(biolip_df) - grouped_biolip = biolip_df.groupby("pdb_id") - pdb_list = list(grouped_biolip.groups.keys()) - done_list = { - tuple(os.path.basename(f).split("_")[:2]) - for f in glob.glob(output_path + "*.pdb") - } - for pdb_count in range(start_pdb, end_pdb): - # pdb_id = random.choice(list(grouped_biolip.groups.keys())) - pdb_id = pdb_list[pdb_count] - rows = grouped_biolip.get_group(pdb_id) - print(f"preparing {pdb_id} (entry: {pdb_count})") - prepped_pdb_fnames = set() - for idx, row in rows.iterrows(): - sys.stdout.flush() - bs_counter = row["receptor_chain"] + row["binding_site_number_code"] - if (pdb_id, bs_counter) in done_list: - continue - try: - st, fname = get_prepped_protein(pdb_id, row, fill_sidechain) - except RuntimeError as e: - print(f"Error on {pdb_id}, {bs_counter}: PrepWizard failed") - print(e) - continue - except ConnectionError: - print( - f"Error on {pdb_id}, {bs_counter}: Could not reach PDB server, try again later?" - ) - continue - except ValueError: - print(f"Error on {pdb_id}, {bs_counter}: BioLiP chain error") - continue - else: - prepped_pdb_fnames.add(fname) - - try: - lig_ats, res_ats = get_atom_lists(st, row) - except MissingAtomsError: - print(f"Error on {pdb_id}, {bs_counter}: Atoms are missing") - continue - except MissingResiduesError as e: - print(f"Error on {pdb_id}, {bs_counter}: {e} residue is missing") - continue - except MutateError: - print( - f"Error on {pdb_id}, {bs_counter}: Cannot mutate gap residue to GLY" - ) - continue - - # Count heavy atoms of ligand and skip if too large - heavy_lig_ats = [at for at in lig_ats if st.atom[at].atomic_number > 1] - if len(heavy_lig_ats) > ligand_size_limit: - print("ligand too big: ", len(heavy_lig_ats)) - continue - - # Do the extraction - print(f"obtaining {pdb_id}, binding site {bs_counter}") - ligand_env = st.extract(lig_ats + res_ats) - try: - cap_termini(st, ligand_env) - except Exception as e: - print(f"Error on {pdb_id}, {bs_counter}: Cannot cap termini") - print(e) - continue - ligand_env = build.reorder_protein_atoms_by_sequence(ligand_env) - fname = os.path.join( - output_path, - f"{pdb_id}_{bs_counter}_{ligand_env.formal_charge}.pdb", - ) - ligand_env.write(fname) - - # Cleanup the remaining prepped files for this pdb_id - print("done with", pdb_count, pdb_id) - for fname in prepped_pdb_fnames.union([f'{pdb_id}.pdb', f'{pdb_id}.cif']): - if os.path.exists(fname): - os.remove(fname) - - -def download_cif(pdb_id: str) -> Structure: - """ - Download cif (as opposed to pdb) of a given protein and extract - the needed chains. - - :param pdb_id: name of PDB to download - :return: Downloaded structure - """ - - # Try for the PDB - fname = f"{pdb_id}.pdb" - if not os.path.exists(fname): - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) - if os.path.exists(fname): - st = next(StructureReader(fname), None) - if st is not None: - return st - - # Failing that, take the CIF - fname = f"{pdb_id}.cif" - if not os.path.exists(fname): - for i in range(3): - subprocess.run( - [os.path.join(SCHRO, "utilities", "getpdb"), pdb_id, "-format", "cif"] - ) - if os.path.exists(fname): - break - else: - time.sleep(10) - else: - raise ConnectionError - - st = next(StructureReader(fname), None) - if st is None: - raise ConnectionError - return st - - -def get_prepped_protein( - pdb_id: str, row: pd.Series, fill_sidechain: bool = True, prep: bool = True -) -> Tuple[Structure, str]: - """ - Obtain a structure of the protein suitable for atomistic calculations - - This requires correct hydrogens on ligands and protein residues, proper - accounting for charge, formation of any disulfide bonds or zero-order bonds - to metals. - - :param pdb_id: PDB name to be obtained - :param row: Series containing receptor and ligand information - :param fill_sidechain: If True, PrepWizard will try and fill in missing - side chains. Note, this can actually delete covalently - attached ligands. - :param prep: If False, preparation steps can be skipped and we only - download a PDB as is - :return: Prepared structure and its filename for subsequent clean-up - """ - chains = {row["receptor_chain"], row["ligand_chain"]} - outname = f"{pdb_id}_{'_'.join(sorted(chains))}_prepped.maegz" - maename = f"{pdb_id}.maegz" - - if not prep: - subprocess.run([os.path.join(SCHRO, "utilities", "getpdb"), pdb_id]) - outname = f"{pdb_id}.pdb" - elif os.path.exists(outname): - # We've already done this example - pass - else: - # We haven't done anything to prepare the protein - st = download_cif(pdb_id) - - # only extract the relevant chains because these proteins can be large - # and then PrepWizard can take hours - at_list = [] - try: - for chain in chains: - at_list.extend(st.chain[chain].getAtomList()) - except KeyError: - print(f"Chain is missing from {pdb_id}") - raise ValueError - st = st.extract(at_list) - - # Remove any dummy atoms, PrepWizard doesn't like them - dummy_atoms = [at for at in st.atom if at.atomic_number < 1] - st.deleteAtoms(dummy_atoms) - st.write(maename) - - # Run PrepWizard - if not os.path.exists(outname): - # We have to check for outname existence again because the proper outname - # for PDBs that have to be downloaded as CIFs isn't known until after - # we download them and can see their chain names. - try: - run_prepwizard(maename, outname, fill_sidechain) - except subprocess.TimeoutExpired: - raise RuntimeError("PrepWizard took longer than 2 hours, skipping") - if not os.path.exists(outname): - raise RuntimeError("PrepWizard failed") - - st = StructureReader.read(outname) - st = build.remove_alternate_positions(st) - if deprotonate_phosphate_esters(st): - print( - f'{pdb_id}, {row["receptor_chain"]}{row["binding_site_number_code"]} needed phosphate deprotonation' - ) - if deprotonate_carboxylic_acids(st): - print( - f'{pdb_id}, {row["receptor_chain"]}{row["binding_site_number_code"]} needed carboxylic acid deprotonation' - ) - st = build.reorder_protein_atoms_by_sequence(st) - - # Cleanup - for file_to_del in (maename,): - if os.path.exists(file_to_del): - os.remove(file_to_del) - for deldir in glob.glob(f"{pdb_id}-???"): - shutil.rmtree(deldir) - sys.stdout.flush() - return st, outname - - -def run_prepwizard(fname: str, outname: str, fill_sidechain: bool) -> None: - """ - Run Schrodinger's PrepWizard - - In most cases, this seems to run in a handful of seconds to a few minutes. - In a few extreme examples, it took hours or days. Since this holds up processing - for the entire batch, we will add a 2 hour time-limit with PROPKA and an additional - 2 hour time-limit not using PROPKA (which seems to frequently be were things get bogged - down, though it may also be in H-Bond optimization). - - :param fname: input file name for PrepWizard - :param outname: output file name from PrepWizard - :param fill_sidechain: If True, try to fill in side chains - """ - args = [ - os.path.join(SCHRO, "utilities", "prepwizard"), - fname, - outname, - "-noepik", - "-noimpref", - "-disulfides", - "-NOJOBID", - ] - if fill_sidechain: - args.append("-fillsidechains") - try: - subprocess.run( - args, - timeout=3600 * 2, # Wait not more than 2 hours - ) - except subprocess.TimeoutExpired: - # Try again without PROPKA (which seems to be where things get stuck) - print("PrepWizard is taking too long, try without PROPKA") - args.append("-nopropka") - subprocess.run( - args, - timeout=3600 * 2, # Wait not more than 2 hours - ) - - -def deprotonate_carboxylic_acids(st: Structure) -> bool: - """ - At physiological pH, it's a good assumption that any carboxylic acids - will be deprotonated. In the absence pKa's for ligands, we will make - this assumption. - - :param st: Structure with carboxylic acid groups that can be deprotonated - :return: True if structure needed to be deprotonated - """ - cooh_smarts = "[C](=[O])([O][H])" - try: - matched_ats = evaluate_smarts(st, cooh_smarts) - except ValueError: - matched_ats = [] - H_ats = {ats[-1] for ats in matched_ats} - O_ats = {ats[-2] for ats in matched_ats} - for O_at in O_ats: - st.atom[O_at].formal_charge -= 1 - st.deleteAtoms(H_ats) - return bool(H_ats) - - -def deprotonate_phosphate_esters(st: Structure) -> bool: - """ - At physiological pH, it's a good assumption that any phosphate esters - will be deprotonated. In the absence pKa's for ligands, we will make - this assumption. - - :param st: Structure with phosphate groups that can be deprotonated - :return: True if structure needed to be deprotonated - """ - phos_smarts = "[*;!#1][*][P](=[O,S])([O])([O][H])" - try: - matched_ats = evaluate_smarts(st, phos_smarts) - except ValueError: - matched_ats = [] - H_ats = {ats[-1] for ats in matched_ats} - O_ats = {ats[-2] for ats in matched_ats} - for O_at in O_ats: - st.atom[O_at].formal_charge -= 1 - st.deleteAtoms(H_ats) - return bool(H_ats) - - -def make_gaps_gly(st: Structure, row: pd.Series, gap_res: List[str]) -> None: - """ - Turn gap residues into glycines - - If we have a single residue which would not normally be included - which is between two which are, then the capping groups of those - two are going to overlap because they are both trying to fill in - the same missing CA. As such, we should just include that missing - single gap residue as a glycine (it's actually smaller than two - capping groups). - - If that gap residue is something non-standard (and Schrodinger - considers a lot more than the 20 standard amino acids to be - "standard", e.g. selenomethionine, hydroxyproline are "standard"), - we just leave it as is. - - :param st: Structure being modified - :param row: Series containing receptor and ligand information - :param gap_res: list of residue numbers which are single gaps - """ - for res_num in gap_res: - res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') - # You have to be pretty weird to not be a Standard Residue, - # just keep these as is - if not res.isStandardResidue(): - continue - # If the residue being turned to GLY is not just a simple amino - # acid, e.g. it is bound to a ligand, it can't be mutated properly - # and it will actually also garble the structure - if res.getBetaCarbon() is not None: - if res.getAlphaCarbon() is None: - raise MutateError - st.deleteBond(res.getBetaCarbon(), res.getAlphaCarbon()) - try: - build.mutate(st, res.getAlphaCarbon(), "GLY") - except: - raise MutateError - - -def get_atom_lists(st: Structure, row: pd.Series) -> Tuple[List[int], List[int]]: - """ - Get the lists of ligand atoms and receptor atoms - - :param st: Structure to extract from - :param row: Series containing receptor and ligand information - """ - res_ats = [] - res_list = [res[1:] for res in row["binding_site_residues_pdb"].split()] - gap_res = get_single_gaps(st, row["receptor_chain"], res_list) - make_gaps_gly(st, row, gap_res) - - # Mutating residues can change the atom numbering so let's retreive - # all the atom indices in a separate loop - for res_num in gap_res + res_list: - res = st.findResidue(f'{row["receptor_chain"]}:{res_num}') - if res.hasMissingAtoms(): - print(f'Missing atoms in rec res {row["receptor_chain"]}:{res_num}') - raise MissingAtomsError - res_ats.extend(res.getAtomIndices()) - - lig_ats = [] - for res_num in range(row["ligand_residue_number"], row["ligand_residue_end"] + 1): - res_name = f'{row["ligand_chain"]}:{res_num}{row["ligand_residue_inscode"]}' - try: - res = st.findResidue(res_name) - except ValueError: - print(f"missing expected ligand residue: {res_name}") - raise MissingResiduesError("Ligand") - lig_ats.extend(res.getAtomIndices()) - # Add in coordinating groups for ions - coord_ats = [] - if len(lig_ats) == 1: - asl_str = f"fillres within 3 atom.num {lig_ats[0]}" - coord_ats = [ - at for at in analyze.evaluate_asl(st, asl_str) if at not in res_ats - ] - - # mark the protein as unused, we will edit the parts we want - for ch in st.chain: - ch.name = "X" - # mark the coord chain - for at in coord_ats: - st.atom[at].chain = "c" - # mark the ligand chain - for at in lig_ats: - st.atom[at].chain = "l" - # mark the receptor chain - for at in res_ats: - st.atom[at].chain = "A" - - return lig_ats + coord_ats, res_ats - - -def get_single_gaps(st: Structure, rec_chain: str, res_list: List[str]) -> List[str]: - """ - Get residues that are not in a list of residues but are - between two residues which are in the list. - - If we have a single residue which would not normally be included - which is between two which are, then the capping groups of those - two are going to overlap because they are both trying to fill in - the same missing CA (the CA of the gap residue). We need to treat - these specially so we retrieve them here. - - :param st: structure to analyze - :param rec_chain: name of receptor chain - :param res_list: list of residue names which may have single-residue gaps - :return: list of residues which are single-residue gaps in `res_list` - """ - parent_indices = set() - try: - parent_list = list(st.chain[rec_chain].residue) - except KeyError: - print(f"missing expected receptor chain: {rec_chain}") - raise MissingResiduesError("Chain") - for res_name in res_list: - try: - res = st.findResidue(f"{rec_chain}:{res_name}") - except ValueError: - print(f"missing expected receptor residue: {rec_chain}:{res_name}") - raise MissingResiduesError("Receptor") - parent_indices.add(parent_list.index(res)) - gaps = [ - val + 1 - for val in parent_indices - if val + 1 not in parent_indices and val + 2 in parent_indices - ] - gap_res = [f"{parent_list[gap].resnum}{parent_list[gap].inscode}" for gap in gaps] - return gap_res - - -def cap_termini(st: Structure, ligand_env: Structure) -> None: - """ - Cap termini for extracted receptor chains with NMA or ACE oriented to match - the positions of neighboring residues in the original structure. - - :param st: original protein structure from which the pocket was extracted - :param ligand_env: extracted protein receptor (i.e. ligand environment) - """ - capterm = CapTermini(ligand_env, verbose=False, frag_min_atoms=3) - for res in capterm.cappedResidues(): - orig_res = st.findResidue(res) - new_res = ligand_env.findResidue(res) - try: - val = st.measure(*orig_res.getDihedralAtoms("Psi")) - ligand_env.adjust(val, *new_res.getDihedralAtoms("Psi")) - - val = st.measure(*reversed(orig_res.getDihedralAtoms("Phi"))) - ligand_env.adjust(val, *reversed(new_res.getDihedralAtoms("Phi"))) - except: - pass - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument("--start_idx", type=int, required=True) - parser.add_argument("--end_idx", type=int, required=True) - parser.add_argument("--output_path", default=".") - parser.add_argument( - "--no_fill_sidechain", dest="fill_sidechain", action="store_false" - ) - return parser.parse_args() - - -def main(): - args = parse_args() - biolip_df = get_biolip_db(pklpath=args.output_path) - retreive_ligand_and_env( - biolip_df, - start_pdb=args.start_idx, - end_pdb=args.end_idx, - output_path=args.output_path, - fill_sidechain=args.fill_sidechain, - ) - - -if __name__ == "__main__": - main() diff --git a/biomolecules/pdb_pockets/cleanup.py b/biomolecules/pdb_pockets/cleanup.py deleted file mode 100644 index 73a2036..0000000 --- a/biomolecules/pdb_pockets/cleanup.py +++ /dev/null @@ -1,340 +0,0 @@ -import argparse -import glob -import os - -from schrodinger.application.jaguar.utils import mmjag_update_lewis -from schrodinger.structure import Structure, StructureReader -from schrodinger.structutils import build, measure -from schrodinger.structutils.analyze import evaluate_asl, evaluate_smarts -from tqdm import tqdm - - -def remove_extra_Hs(st: Structure) -> bool: - ats_to_delete = [] - for pair in measure.get_close_atoms(st, dist=0.5): - at1, at2 = sorted(pair, key=lambda x: st.atom[x].atomic_number) - if ( - st.atom[at1].atomic_number == 1 - and st.atom[at2].atomic_number == 6 - and st.atom[at2].bond_total > 4 - and st.areBound(at1, at2) - ): - ats_to_delete.append(at1) - if ats_to_delete: - st.deleteAtoms(ats_to_delete) - return True - return False - - -def rename_coord_chain(st): - chain_names = [ch.name for ch in st.chain] - if "l" not in chain_names and "c" in chain_names: - lig = [] - if len(st.chain["c"].getAtomList()) == 1: - lig = st.chain["c"].getAtomList() - if not lig: - lig = evaluate_asl(st, "chain c and metals") - if not lig: - lig = evaluate_asl(st, "chain c and res D8U") - if not lig: - lig = evaluate_asl(st, "chain c and atom.ato >=18") - if not lig: - lig = evaluate_asl(st, "chain c and atom.ele F,Cl,Br,I") - for at in lig: - st.atom[at].chain = "l" - if lig: - return True - - -def deprotonate_metal_bound_n(st): - N_to_dep = evaluate_asl( - st, - "atom.ele N and atom.att 4 and (withinbonds 1 metals) and (withinbonds 1 atom.ele H)", - ) - ats_to_del = [] - for at_N in N_to_dep: - att_H = next( - b_at for b_at in st.atom[at_N].bonded_atoms if b_at.atomic_number == 1 - ) - ats_to_del.append(att_H) - st.atom[at_N].formal_charge = -1 - st.deleteAtoms(ats_to_del) - return bool(N_to_dep) - - -def deprotonate_carboxylic_acids(st: Structure) -> bool: - """ - At physiological pH, it's a good assumption that any carboxylic acids - will be deprotonated. In the absence pKa's for ligands, we will make - this assumption. - - :param st: Structure with carboxylic acid groups that can be deprotonated - :return: True if structure needed to be deprotonated - """ - cooh_smarts = "[C](=[O])([O][H])" - try: - matched_ats = evaluate_smarts(st, cooh_smarts) - except ValueError: - matched_ats = [] - H_ats = {ats[-1] for ats in matched_ats} - O_ats = {ats[-2] for ats in matched_ats} - for O_at in O_ats: - st.atom[O_at].formal_charge -= 1 - st.deleteAtoms(H_ats) - return bool(H_ats) - - -def fix_heme_charge(st): - change_made = False - for res in st.chain["l"].residue: - if res.pdbres.strip() in {"HEM", "HEC"}: - coord_n = [res.getAtomByPdbName(f" N{i} ") for i in "ABCD"] - if any(at is None for at in coord_n): - continue - if sum(at.formal_charge for at in coord_n) != -2: - for i, at in enumerate(coord_n, 1): - at.formal_charge = -1 * (i % 2) - change_made = True - return change_made - - -def fix_quartenary_N_charge(st): - quart_N = evaluate_smarts(st, "[NX4+0]") - for at_N in quart_N: - if all(bond.order == 1 for bond in st.atom[at_N[0]].bond): - st.atom[at_N[0]].formal_charge = 1 - return bool(quart_N) - - -def non_physical_estate(st): - change_made = False - if (sum(at.atomic_number for at in st.atom) - st.formal_charge) % 2 != 0: - ats_before = st.atom_total - build.add_hydrogens(st) - if ats_before != st.atom_total: - change_made = True - else: - mmjag_update_lewis(st) - ats_before = st.atom_total - build.add_hydrogens(st) - if ats_before != st.atom_total: - change_made = True - return change_made - - -def merge_chain_names(st, at1, at2): - chains = [at1.chain, at2.chain] - if len(set(chains)) != 1: - main_chains = [chain for chain in chains if chain.isupper()] - if len(main_chains) == 1: - main_chain = main_chains.pop() - if at1.chain == main_chain: - old_mol = at2.molecule_number - else: - old_mol = at1.molecule_number - old_chain = next(chain for chain in chains if chain != main_chain) - for at in st.molecule[old_mol].atom: - if at.chain == old_chain: - at.chain = main_chain - - -def remove_total_overlaps(st): - ats_to_delete = [ - max(at1, at2) for at1, at2 in measure.get_close_atoms(st, dist=0.05) - ] - if ats_to_delete: - st.deleteAtoms(ats_to_delete) - return True - return False - - -def meld_ace_nma(st): - change_made = False - at_pairs = measure.get_close_atoms(st, dist=0.5) - while at_pairs: - at1, at2 = at_pairs.pop() - at1, at2 = (st.atom[at1], st.atom[at2]) - if ( - {at1.atomic_number, at2.atomic_number} == {6} - and {at1.pdbres.strip(), at2.pdbres.strip()} == {"ACE", "NMA"} - and {at1.pdbname.strip(), at2.pdbname.strip()} == {"CA", "CH3"} - ): - # Renumber chains if necessary - merge_chain_names(st, at1, at2) - - if at1.pdbname.strip() == "CA": - keep_at = at1 - del_at = at2 - else: - keep_at = at2 - del_at = at1 - for at in keep_at.getResidue().getAtomList(): - st.atom[at].resnum = del_at.resnum - st.atom[at].inscode = del_at.inscode - for at in at1.getResidue().getAtomList() + at2.getResidue().getAtomList(): - st.atom[at].pdbres = "GLY " - del_Hs = [b_at for b_at in del_at.bonded_atoms if b_at.atomic_number == 1] - del_Hs.extend( - [b_at for b_at in keep_at.bonded_atoms if b_at.atomic_number == 1] - ) - non_H = next( - b_at for b_at in del_at.bonded_atoms if b_at.atomic_number != 1 - ) - st.addBond(keep_at, non_H, 1) - st.deleteAtoms(del_Hs + [del_at]) - build.add_hydrogens(st, atom_list=[keep_at]) - at_pairs = measure.get_close_atoms(st, dist=0.5) - change_made = True - return change_made - - -def reconnect_open_chains(st: Structure): - broken_C = evaluate_asl( - st, - "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l", - ) - broken_N = evaluate_asl( - st, - "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l", - ) - change_made = False - while broken_C: - change_made = True - b_C = broken_C.pop() - for b_N in broken_N: - if st.measure(b_C, b_N) < 1.5 and not st.areBound(b_C, b_N): - st.addBond(b_C, b_N, 1) - st.atom[b_C].formal_charge = 0 - st.atom[b_N].formal_charge = 0 - merge_chain_names(st, st.atom[b_C], st.atom[b_N]) - broken_C = evaluate_asl( - st, - "atom.pt C and atom.att 2 and within 1.5 (atom.pt N and atom.att 2 and not chain l) and not chain l", - ) - broken_N = evaluate_asl( - st, - "atom.pt N and atom.att 2 and within 1.5 (atom.pt C and atom.att 2 and not chain l) and not chain l", - ) - break - return change_made - - -def fix_disrupted_disulfides(st: Structure) -> bool: - """ - If a cysteine sulfur is missing a hydrogen, add it. - - This occurs when a cysteine residue which is part of a disulfide - bond is extracted but its corresponding partner is not, leaving - a "bare" S. - - :param st: Structure to correct - :return: If a change was made, return True - """ - broken_cysteines = evaluate_asl(st, "atom.pt SG and atom.att 1") - if broken_cysteines: - build.add_hydrogens(st, atom_list=broken_cysteines) - return True - return False - - -def remove_ligand_ace_cap(st: Structure) -> bool: - """ - If there is an ACE added to a ligand (and the ACE is not itself the ligand), - remove it and recover what is likely a protonated N. - - :param st: Structure to correct - :return: If a change was made, return True - """ - ats_to_delete = [] - N_to_protonate = [] - for res in st.chain["l"].residue: - if res.pdbres.strip() == "ACE" and len(st.chain["l"].getAtomList()) != 6: - capped_N = next( - (at for at in res.getCarbonylCarbon().bonded_atoms if at.element == "N") - ) - ats_to_delete.extend(res.getAtomList()) - N_to_protonate.append(capped_N) - for at in N_to_protonate: - st.atom[at].formal_charge += 1 - if N_to_protonate: - st.deleteAtoms(ats_to_delete) - build.add_hydrogens(st, atom_list=N_to_protonate) - return True - return False - - -def remove_ligand_nma_cap(st: Structure) -> bool: - """ - If there is an NMA added to a ligand (and the ligand is not NMA), - remove it and recover what is likely a deprotonated O. - - :param st: Structure to correct - :return: If a change was made, return True - """ - ats_to_delete = [] - for res in st.chain["l"].residue: - if res.pdbres.strip() == "NMA" and len(res.getAtomList()) == 6: - n_at = res.getBackboneNitrogen() - if n_at is None: - raise RuntimeError - ats_to_delete.extend(res.getAtomList()) - ats_to_delete.remove(n_at.index) - n_at.element = "O" - n_at.formal_charge = -1 - for b_at in n_at.bonded_atoms: - adj_res = b_at.getResidue() - if adj_res != res: - break - n_at.resnum = adj_res.resnum - n_at.inscode = adj_res.inscode - n_at.pdbres = adj_res.pdbres - n_at.pdbname = "" - st.deleteAtoms(ats_to_delete) - return bool(ats_to_delete) - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument("--output_path", default=".") - parser.add_argument("--prefix", default="") - parser.add_argument("--batch", type=int, default=0) - parser.add_argument("--nuclear_option", action="store_true") - return parser.parse_args() - - -def main(): - args = parse_args() - file_list = glob.glob(os.path.join(args.output_path, f"{args.prefix}*.pdb")) - file_list = file_list[10000 * args.batch : 10000 * (args.batch + 1)] - for fname in tqdm(file_list): - if not os.path.exists(fname): - continue - st = StructureReader.read(fname) - change_made = rename_coord_chain(st) - change_made = fix_disrupted_disulfides(st) or change_made - change_made = deprotonate_carboxylic_acids(st) or change_made - change_made = remove_ligand_ace_cap(st) or change_made - change_made = remove_ligand_nma_cap(st) or change_made - change_made = remove_extra_Hs(st) or change_made - change_made = meld_ace_nma(st) or change_made - change_made = reconnect_open_chains(st) or change_made - change_made = remove_total_overlaps(st) or change_made - change_made = fix_quartenary_N_charge(st) or change_made - if args.nuclear_option: - change_made = deprotonate_metal_bound_n(st) or change_made - change_made = fix_heme_charge(st) or change_made - change_made = non_physical_estate(st) or change_made - if change_made: - new_fname = os.path.join( - os.path.dirname(fname), - "_".join(os.path.basename(fname).split("_")[:-1]), - ) - new_fname += f"_{st.formal_charge}.pdb" - print(f"{fname} -> {new_fname}") - st = build.reorder_protein_atoms_by_sequence(st) - os.remove(fname) - st.write(new_fname) - - -if __name__ == "__main__": - main() diff --git a/biomolecules/pdb_pockets/combine_pockets.py b/biomolecules/pdb_pockets/combine_pockets.py deleted file mode 100644 index 85f9a2d..0000000 --- a/biomolecules/pdb_pockets/combine_pockets.py +++ /dev/null @@ -1,169 +0,0 @@ -import argparse -import glob -import os -from typing import Optional - -import pandas as pd -from schrodinger.structure import Structure, StructureReader -from schrodinger.structutils import measure -from tqdm import tqdm - -from biolip_extraction import get_biolip_db - - -def combine_pockets(biolip_df: pd.DataFrame, path: str): - """ - Combine entries that correspond to the same pocket. - - If a ligand is interacting with multiple receptor chains, they will - appear as different entries in BioLiP and therefore different structures - here. We should combine such structures into one structure. - - :param biolip_df: DataFrame storing BioLiP database - :param path: Path to extracted pockets - """ - shared_pockets = biolip_df[ - biolip_df.duplicated( - subset=["pdb_id", "ligand_id", "ligand_chain", "ligand_residue_number"], - keep=False, - ) - ] - grouped_pockets = shared_pockets.groupby( - ["pdb_id", "ligand_id", "ligand_chain", "ligand_residue_number"], - group_keys=False, - ) - file_list = glob.glob(os.path.join(path, "*.pdb")) - for key, item in tqdm(grouped_pockets): - old_names = [] - combined_st = None - out_name = key[0] - count = 0 - for idx, row in item.iterrows(): - bs_name = f'{row["receptor_chain"]}{row["binding_site_number_code"]}' - start = os.path.join(path, f'{row["pdb_id"]}_{bs_name}_') - fname = [ - f - for f in file_list - if f.startswith(start) and len(os.path.basename(f).split("_")) == 3 - ] - if not fname: - continue - assert len(fname) == 1 - fname = fname.pop() - st = StructureReader.read(fname) - try: - combined_st = merge_structures(combined_st, st, count) - except KeyError: - print(fname) - print(old_names) - raise - count += 1 - old_names.append(fname) - out_name += f"_{bs_name}" - if combined_st is not None: - out_name += f"_{combined_st.formal_charge}" - for fname in old_names: - os.remove(fname) - combined_st.write(os.path.join(path, out_name + ".pdb")) - - -def get_ligand_chain_bonds(st: Structure) -> dict[int:tuple]: - """ - Get bonds between ligand and receptor chains - - We will need to copy these bonds into the combined structure, as we - have only one copy of the ligand and potentially multiple attachment - sites. - - :param st: Structure to get bonds in - :return: Dictionary relating the index of the ligand atom to a tuple - of the StructureAtom object (so that new numbering can be - extracted when atoms are deleted) and bond order (which would - disappear if one of the atoms were deleted) - """ - comb_cov = {} - for bond in st.bond: - chains = {at.chain for at in bond.atom} - if "l" in chains and any(ch.isupper() for ch in chains): - if bond.atom1.chain == "l": - comb_cov[bond.atom1.index] = (bond.atom2, bond.order) - else: - comb_cov[bond.atom2.index] = (bond.atom1, bond.order) - return comb_cov - - -def merge_structures( - combined_st: Optional[Structure], st: Structure, count: int -) -> Structure: - """ - Merge the structures - - This requires: - 1) Determining what ligand-receptor bonds are present in `st` - 2) Deleting duplicated atoms (i.e. the ligand and any coordinating atoms) from `st` - 3) Combining `combined_st` and `st` - 4) Recovering ligand-receptor bonds which may have been deleted in Step 2 - 5) If the newly added chain had previously been picked up as - coordinating atoms, remove those coordinating atoms in favor - of the equivalent receptor atoms - - :param combined_st: Structure (or None if we are just starting) to - collect combined structure into - :param st: Structure to add to combined_st - :param count: How many structures have been added (this is to keep track of chain names) - :return: Newly combined structure - """ - if combined_st is None: - return st - # Get covalent bonds between ligands and receptor chains - new_cov = get_ligand_chain_bonds(st) - - # Figure out the equivalent atom numbers between - comb_copy = combined_st.copy() - comb_copy.extend(st) - offset = combined_st.atom_total - remapped_cov = {} - for pair in measure.get_close_atoms(comb_copy, dist=0.01): - if max(pair) - offset in new_cov: - remapped_cov[min(pair)] = new_cov[max(pair) - offset] - - # delete ligand atoms - ligand_ats = st.chain["l"].getAtomList() - if "c" in (ch.name for ch in st.chain): - ligand_ats.extend(st.chain["c"].getAtomList()) - st.deleteAtoms(ligand_ats) - for at in st.atom: - at.chain = chr(65 + count) - - # combine structures and recover ligand-receptor bonds - combined_st.extend(st) - for lig_at, (chain_at, order) in remapped_cov.items(): - if not combined_st.areBound(lig_at, chain_at.index + offset): - combined_st.addBond(lig_at, chain_at.index + offset, order) - - # Resolve any coordinating atoms in favor of a receptor atom - close_atoms = measure.get_close_atoms(combined_st, dist=0.05) - ats_to_delete = [] - for at1, at2 in close_atoms: - if combined_st.atom[at2].chain == "c": - ats_to_delete.append(at2) - elif combined_st.atom[at1].chain == "c": - ats_to_delete.append(at1) - combined_st.deleteAtoms(ats_to_delete) - return combined_st - - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument("--output_path", default=".") - return parser.parse_args() - - -def main(): - args = parse_args() - biolip_df = get_biolip_db(pklpath=args.output_path) - combine_pockets(biolip_df, args.output_path) - - -if __name__ == "__main__": - main() diff --git a/biomolecules/pdb_pockets/desmond_md.cfg b/biomolecules/pdb_pockets/desmond_md.cfg deleted file mode 100644 index 35b9966..0000000 --- a/biomolecules/pdb_pockets/desmond_md.cfg +++ /dev/null @@ -1,91 +0,0 @@ -annealing = false -backend = { -} -bigger_rclone = false -box = ? -checkpt = { - first = 0.0 - interval = 240.06 - name = "$JOBNAME.cpt" - write_last_step = true -} -cpu = 1 -cutoff_radius = 9.0 -dipole_moment = false -ebias_force = false -elapsed_time = 0.0 -energy_group = false -eneseq = { - first = 0.0 - interval = 1.2 - name = "$JOBNAME$[_replica$REPLICA$].ene" -} -ensemble = { - barostat = { - tau = 2.0 - } - class = NVT - method = Langevin - thermostat = { - tau = 1.0 - } -} -gaussian_force = false -glue = solute -lambda_dynamics = false -maeff_output = { - center_atoms = solute - first = 0.0 - interval = 120.0 - name = "$JOBNAME$[_replica$REPLICA$]-out.cms" - periodicfix = true - trjdir = "$JOBNAME$[_replica$REPLICA$]_trj" -} -meta = false -meta_file = ? -msd = false -pressure = 1.01325 -pressure_tensor = false -randomize_velocity = { - first = 0.0 - interval = inf - seed = 2007 - temperature = "@*.temperature" -} -restraints = { - existing = ignore - new = [ - { - name = posre_harm - atoms = ["atom.pt CA or (res ACE and atom.pt CH3)"] - force_constants = [100 100 100] - } - ] -} -rnemd = false -simbox = { - first = 0.0 - interval = 1.2 - name = "$JOBNAME$[_replica$REPLICA$]_simbox.dat" -} -spatial_temperature = false -surface_tension = 0.0 -taper = false -temperature = [ - [300.0 0 ] -] -time = 1020.0 -timestep = [0.002 0.002 0.006 ] -trajectory = { - center = [] - first = 0.0 - format = dtr - frames_per_file = 250 - interval = 10.0 - name = "$JOBNAME$[_replica$REPLICA$]_trj" - periodicfix = true - write_last_vel = false - write_velocity = false -} -wall_force = false - diff --git a/biomolecules/pdb_pockets/desmond_md.msj b/biomolecules/pdb_pockets/desmond_md.msj deleted file mode 100644 index 8508bdb..0000000 --- a/biomolecules/pdb_pockets/desmond_md.msj +++ /dev/null @@ -1,100 +0,0 @@ -# Desmond standard NVT relaxation protocol -# All times are in the unit of ps. -# Energy is in the unit of kcal/mol. -task { - task = "desmond:auto" - set_family = { - desmond = { - checkpt.write_last_step = no - } - } -} - -build_geometry { - box = { - shape = orthorhombic - size = [50.0 50.0 50.0 ] - size_type = buffer - } - neutralize_system = false - override_forcefield = OPLS_2005 - rezero_system = false - solvate_system = false -} - -assign_forcefield { - forcefield = OPLS_2005 -} - -simulate { - title = "Brownian Dynamics NVT, T = 10 K, small timesteps, and restraints on solute heavy atoms, 100ps" - annealing = off - time = 100 - timestep = [0.001 0.001 0.003 ] - temperature = 10.0 - ensemble = { - class = "NVT" - method = "Brownie" - brownie = { - delta_max = 0.1 - } - } - restraints.new = [{ - name = posre_harm - atoms = solute_heavy_atom - force_constants = 50.0 - }] -} - - -simulate { - title = "NVT, T = 10 K, small timesteps, and restraints on solute heavy atoms, 12ps" - annealing = off - time = 12 - timestep = [0.001 0.001 0.003] - temperature = 10.0 - restraints.new = [{ - name = posre_harm - atoms = solute_heavy_atom - force_constants = 50.0 - }] - ensemble = { - class = NVT - method = Langevin - thermostat.tau = 0.1 - } - - randomize_velocity.interval = 1.0 - eneseq.interval = 0.3 - trajectory.center = solute -} - -simulate { - title = "Minimization, 100ps" - annealing = off - time = 100 - timestep = [0.001 0.001 0.003 ] - temperature = 10.0 - ensemble = { - class = "NVT" - method = "Brownie" - brownie = { - delta_max = 0.1 - } - thermostat = { - tau = 1.0 - } - } - restrain = none - restraints = { - existing = ignore - new = [] - } -} -simulate { - cfg_file = "/private/home/levineds/om-data/biomolecules/pdb_pockets/desmond_md.cfg" - jobname = "$MAINJOBNAME" - dir = "." - compress = "" -} - diff --git a/biomolecules/pdb_pockets/run_md.py b/biomolecules/pdb_pockets/run_md.py deleted file mode 100644 index b97dd85..0000000 --- a/biomolecules/pdb_pockets/run_md.py +++ /dev/null @@ -1,18 +0,0 @@ -import argparse -import glob -import os - -def parse_args(): - parser = argparse.ArgumentParser() - parser.add_argument("--output_path", default=".") - return parser.parse_args() - - -def main(): - args = parse_args() - file_list = glob.glob(os.path.join(args.output_path, f"*.mae")) - with open('paths_list.txt', 'w') as fh: - fh.write('\n'.join(file_list)) - -if __name__ == "__main__": - main() diff --git a/electrolytes/__init__.py b/electrolytes/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/electrolytes/functionalization/README.md b/electrolytes/functionalization/README.md deleted file mode 100644 index cb0f2de..0000000 --- a/electrolytes/functionalization/README.md +++ /dev/null @@ -1,32 +0,0 @@ -# Electrolyte-like functional group substitution - -This module contains a standalone script, `substitutions.py`, that will generate new electrolyte-like molecules by adding functional groups from a pre-defined list to a core template, where the template reflects structures used in the electrolyte literature. Functional group addition is basically random, but: -- In general, selection is biased such that small functional groups are preferred over large ones -- Molecules with uncommon bonding patterns are (sometimes, randomly) removed from the pool of generated molecules -- Certain types of molecules (namely, highly energetic molecules) are excluded - -The included Jupyter notebook, `functional_group_substitution.ipynb`, is mainly for visualization of the templates and functional groups used in `substitutions.py`. - -## Running `substitutions.py` - -`substitutions.py` contains predefined sets of templates and substituents and requires no additional setup from the user. To run: - -``` -python substitutions.py\ ---seed \ ---dump_path \ ---attempts_per_template \ ---attempts_per_template_ood \ ---max_heavy_atoms -``` - -Note that most parameters have defaults (run `substitutions.py -h` for descriptions of these parameters). Further note that, if you want to limit the total number of atoms, rather than the number of heavy (non-H) atoms, you can instead use the flag `--max_atoms `. Note that you cannot use use both `--max_atoms` and `--max_heavy_atoms`. - -## Outputs - -After running `substitutions.py`, the outputs will be found in the directory specified by the `--dump_path` argument. Within that directory will be: - -- A file `initial_library_smiles.json`, containing an (unfiltered) library of generated in-distribution molecules -- A directory `xyz`, which will contain sub-directories with `*.xyz` files for each template. Each `*.xyz` file will have a name like `