This repository contains data and simulation input from the paper:
"Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers"
Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Mathis Bode, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Anda Trifan, Arvind Ramanathan, Rick Stevens, Peter V. Coveney
https://arxiv.org/abs/2103.02843
What follows is a brief description of the contents
Molecular models for four target proteins of SARS-CoV-2 were created for molecular simulations and free energy calculations. They are: 3C like protease (3CLPro), papain-like protease (PLPro), ADP-ribose phosphatase (ADRP), and non-structural protein 15 (NSP15).
100 compounds are studied for each of the proteins, which were chosen from 10,000 docked small molecules, based on their docking scores from the high throughput docking study.
Two apprpaches are applied for the free energy calculatiions:
- ESMACS: Enhanced Sampling of Molecular Dynamics with Approximation of Continuum Solvent
- TIES: Thermodynamic Integration with Enhanced Sampling
Contains .csv files for top 10,000 compounds for each protein target from docking studies, and PDB files for the proteins and the top 100 compounds. The latter are used to create starting structures for the MD simulations.
Forcefield files (mol2 and prep) describing parameterized ligands.
Files related to MMPBSA analysis in tab separated values format.
input- contains the MMPBSA input file used for all analyses3clpro,plpro,adrpandnsp15- contain results for the four protein targets
Amber forcefield topology (prmtop) and coordinate (inpcrd and pdb) files for all ligands (for ESMACS) or ligand pairs (for TIES).