This repository includes scripts to run standard MD using espaloma-0.3
.
This repository is part of espaloma-0.3.0-manuscript.
The robustness and stability of espaloma-0.3
is tested by running simple MD simulations of a protein-ligand complex system (Tyk2 protein).
The RMSD profiles of heavy ligand atoms and C-alpha protein atoms are monitored.
espaloma-0.3
is used to parametrize both the protein and ligand, and openff-2.0.0
is used to assign the LJ parameters.
As a control experiment, the ligand and protein is parametrized with openff-2.1.0
and Amber ff14SB
, respectively.
The initial Tyk2 protein and ligand structures are taken from the custom alchemical protein-ligand binding benchmark dataset (https://github.com/kntkb/protein-ligand-benchmark-custom).
experiment/
: Stores scripts and directories to run and analyze MD trajectories
script/
tyk2-lig_ejm_31/
crd/
espaloma/
openff-2.1.0/
envs/
: Stores conda environment files
environment-0.3.0-v3.yaml
: Conda environment to run Perses with espaloma-0.3
that parameterize both small molecules and proteinsOpenEye toolkit is required to load PBD files into OpenFF Molecule objects. Academic license can be obtained here.
If you find this helpful please cite the following:
@misc{takaba2023machinelearned,
title={Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond},
author={Kenichiro Takaba, Iván Pulido, Pavan Kumar Behara, Chapin E. Cavender, Anika J. Friedman, Michael M. Henry, Hugo MacDermott Opeskin, Christopher R. Iacovella, Arnav M. Nagle, Alexander Matthew Payne, Michael R. Shirts, David L. Mobley, John D. Chodera, Yuanqing Wang},
year={2023},
eprint={2307.07085},
archivePrefix={arXiv},
primaryClass={physics.chem-ph}
}