chargePlacer: Python scripts for charge distribution in Gas-Phase molecular dynamics

This is a command line script to determine a reasonably energy minimised proton sequence for an input PDB file (input) for a given charge state (charge). See Basic Usage. A search algorithm is used to sample proton permutations across chargeable side-chains and termini represented as point charges. The algorithm is inspired by the method described by refs 1–3, it produces a reproducible output proton sequence in far fewer steps than required for sampling all permutations.

Citation

If you use chargePlacer in your research please cite the following article:

Bellamy-Carter J, O'Grady L, Passmore M, Jenner M and Oldham NJ. Decoding Protein Gas‐Phase Stability with Alanine Scanning and Collision Induced Unfolding Ion Mobility Mass Spectrometry. Anal. Sens. (2020). Accepted Author Manuscript. doi:10.1002/anse.202000019

Other Info

A choice of energies are calculated and used for determination:

• By default, E_tot is used. This is the Coulomb energy minus the proton binding energy (i.e. the summed proton affinities of protonated residues). The values used herein are derived from simplified versions of each amino acid, per ref 4. These are PA_NT=886.6, PA_ASP-=1453.5, PA_GLU-=1448.5, PA_HIS=958, PA_LYS=918, PA_ARG=1002, PA_CT-=1430 kJ/mol.
• Coulomb-only is the alternative mode (activated by -c), where only the Coulomb energy is taken into account.

This software also provides the option to perform in silico alanine scanning (activated by -a), where each chargeable side-chain is removed and the minimised proton sequence determined for each 'mutant'.

Both default and alanine_scan modes output two tab-separated files proton_sites.txt and charges.txt.

• proton_sites.txt : A text file listing the side-chains and termini that are protonated in the energy minimised sequence. Each row has the form <RESN> <CHAIN> <RESI>. The energies calculated are included in the file header. This file only ever contains the data for the 'wild-type' protein sequence.
• charges.txt : A text file containing the charges of each residue and terminus in the energy minimised sequence. For the alanine_scan method, each subsequent row contains each mutant variant with the mutated residue charge indicated by nan. An additional file energies.txt is generated in alanine_scan mode, this contains the calculated energies for each charge sequence in charges.txt.

Basic Usage

In the simplest case, a PDB file input is provided along with a target charge state charge. chargePlacer will then import the atom coordinates for pre-defined point charge atoms for all chargeable residues and termini.

python chargePlacer.py input charge

If you move chargePlacer to a directory in your system $PATH then you may omit the python command:

chargePlacer.py input charge

To minimise for Coulomb energy only, append -c:

python chargePlacer.py input charge -c

To perform an alanine_scan, append -a:

python chargePlacer.py input charge -a

If you would like to capture the full output of the program you can use piping:

python chargePlacer.py input charge > log.txt

this may be especially powerful when combined with the verbose option (-v), which will print the energies calculated at each step.

python chargePlacer.py input charge -v > log.txt

See Command Line Options below for further details.

Command Line Options

Required Arguments

Parameter	Description
input, e.g. input.pdb	input PDB file for which to determine charges
charge, e.g. 7	target charge state

Optional arguments

Option	Description
-h, --help	show this help message and exit
-v, --verbose	verbose output
-c, --coulomb_only	minimise for Coulomb repulsion only, ignores proton affinity
-r , --relative_permittivity	relative permittivity to use (default: 1)
-a, --alanine_scan	perform in silico alanine scanning for all chargeable residues
-p, --protect	protect listed chains from alanine scanning, e.g. -p ABC
-o, --output OUTPUT	prefix for output files (default: ""). Gives *proton_sites.txt and *charges.txt

References

1. V. Popa, D. A. Trecroce, R. G. McAllister and L. Konermann, J. Phys. Chem. B, 2016, 120, 5114–5124.
2. M. Bakhtiari and L. Konermann, J. Phys. Chem. B, 2019, 123, 1784–1796.
3. S. K. Fegan and M. Thachuk, J. Chem. Theory Comput., 2013, 9, 2531–2539.
4. A. Moser, K. Range and D. M. York, J. Phys. Chem. B, 2010, 114, 13911–13921.