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| # acpype cache | ||
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| */_date.py | ||
| */_version.py | ||
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Classical Force Field in DMFF" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "DMFF implements classcial molecular mechanics force fields with the following forms:\n", | ||
| "\n", | ||
| "$$\\begin{align*}\n", | ||
| " V(\\mathbf{R}) &= V_{\\mathrm{bond}} + V_{\\mathrm{angle}} + V_\\mathrm{torsion} + V_\\mathrm{vdW} + V_\\mathrm{Coulomb} \\\\\n", | ||
| " &= \\sum_{\\mathrm{bonds}}\\frac{1}{2}k_b(r - r_0)^2 + \\sum_{\\mathrm{angles}}\\frac{1}{2}k_\\theta (\\theta -\\theta_0)^2 + \\sum_{\\mathrm{torsion}}\\sum_{n=1}^4 V_n[1+\\cos(n\\phi - \\phi_s)] \\\\\n", | ||
| " &\\quad+ \\sum_{ij}4\\varepsilon_{ij}\\left[\\left(\\frac{\\sigma_{ij}}{r_{ij}}\\right)^{12} - \\left(\\frac{\\sigma_{ij}}{r_{ij}}\\right)^6\\right] + \\sum_{ij}\\frac{q_iq_j}{4\\pi\\varepsilon_0r_{ij}}\n", | ||
| "\\end{align*}$$" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Import necessary packages" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import jax\n", | ||
| "import jax.numpy as jnp\n", | ||
| "import openmm.app as app\n", | ||
| "import openmm.unit as unit\n", | ||
| "from dmff import Hamiltonian, NeighborList" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Compute energy" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "DMFF uses **OpenMM** to parse input files, including coordinates files, topology specification files. Class `Hamiltonian` inherited from `openmm.ForceField` will be initialized and used to parse force field parameters in XML format. Take parametrzing an organic moleclue with GAFF2 force field as an example.\n", | ||
| "\n", | ||
| "- `lig_top.xml`: Define bond connections (topology). Not necessary if such information is specified in pdb with `CONNECT` keyword.\n", | ||
| "- `gaff-2.11.xml`: GAFF2 force field parameters: bonds, angles, torsions and vdW params\n", | ||
| "- `lig-prm.xml`: Atomic charges" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "app.Topology.loadBondDefinitions(\"lig-top.xml\")\n", | ||
| "pdb = app.PDBFile(\"lig.pdb\")\n", | ||
| "ff = Hamiltonian(\"gaff-2.11.xml\", \"lig-prm.xml\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "The method `Hamiltonian.createPotential` will be called to create differentiable potential energy functions for different energy terms. " | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "potentials = ff.createPotential(\n", | ||
| " pdb.topology,\n", | ||
| " nonbondedMethod=app.NoCutoff\n", | ||
| ")\n", | ||
| "for pot in potentials:\n", | ||
| " print(pot)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "The force field parameters are stored as a Python dict in the `param` attribute of force generators." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "nbparam = ff.getGenerators()[3].params\n", | ||
| "nbparam[\"charge\"] # also \"epsilon\", \"sigma\" etc. keys" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Each generated function will read **coordinates, box, pairs** and force field parameters as inputs. `pairs` is a integer array in which each row specifying atoms condsidered as neighbors within rcut. This can be calculated with `dmff.NeighborList` class which is supported by `jax_md`.\n", | ||
| "\n", | ||
| "The potential energy function will give energy (a scalar, in kJ/mol) as output:\n", | ||
| "\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "positions = jnp.array(pdb.getPositions(asNumpy=True).value_in_unit(unit.nanometer))\n", | ||
| "box = jnp.array([\n", | ||
| " [10.0, 0.0, 0.0], \n", | ||
| " [0.0, 10.0, 0.0],\n", | ||
| " [0.0, 0.0, 10.0]\n", | ||
| "])\n", | ||
| "nbList = NeighborList(box, rc=4)\n", | ||
| "nbList.allocate(positions)\n", | ||
| "pairs = nbList.pairs\n", | ||
| "nbfunc = potentials[-1]\n", | ||
| "energy = nbfunc(positions, box, pairs, ff.getGenerators()[-1].params)\n", | ||
| "print(energy)\n", | ||
| "print(pairs)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "You can also obtain the whole potential energy function and force field parameter set, instead of seperated functions for different energy terms." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "efunc = ff.getPotentialFunc()\n", | ||
| "params = ff.getParameters()\n", | ||
| "totene = efunc(positions, box, pairs, params)\n", | ||
| "totene" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Compute forces and parametric gradients" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Use `jax.grad` to compute forces and parametric gradients automatically" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "pos_grad_func = jax.grad(efunc, argnums=0)\n", | ||
| "force = -pos_grad_func(positions, box, pairs, params)\n", | ||
| "force.shape" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "param_grad_func = jax.grad(nbfunc, argnums=-1)\n", | ||
| "pgrad = param_grad_func(positions, box, pairs, nbparam)\n", | ||
| "pgrad[\"charge\"]" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "interpreter": { | ||
| "hash": "44fe82502fda871be637af1aa98d2b3ddaac01204dd30f1519cbec4e95000815" | ||
| }, | ||
| "kernelspec": { | ||
| "display_name": "Python 3 (ipykernel)", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.7.12" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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