Abstract

Nowadays, drug design projects benefit from highly accurate protein–ligand binding free energy predictions based on molecular dynamics simulations. While such calculations have been computationally expensive in the past, we now demonstrate that workflows built on open source software packages can efficiently leverage pre-exascale computing resources to screen hundreds of compounds in a matter of days. We report our results of free energy calculations on a large set of pharmaceutically relevant targets assembled to reflect industrial drug discovery projects.

[maxbutton id=”4″ url=”https://doi.org/10.1021/acs.jcim.1c01445″ text=”Read more” window=”new” linktitle=”Journal of Chemical Information and Modeling: Pre-Exascale Computing of Protein–Ligand Binding Free Energies with Open Source Software for Drug Design” ]

Citation

Vytautas Gapsys, David F. Hahn, Gary Tresadern, David L. Mobley, Markus Rampp, Bert L. de Groot (2022):
Pre-Exascale Computing of Protein–Ligand Binding Free Energies with Open Source Software for Drug Design.
Journal of Chemical Information and Modeling 62(5) pp. 1172–1177
https://doi.org/10.1021/acs.jcim.1c01445

About the author

Stian works in School of Computer Science, at the University of Manchester in Carole Goble‘s eScience Lab as a technical software architect and researcher. In addition to BioExcel, Stian’s involvements include Open PHACTS (pharmacological data warehouse), Common Workflow Language (CWL), Apache Taverna (scientific workflow system), Linked Data and identifiers, research objects (open science) and digital preservation, myExperiment (sharing scientific workflows), provenance (where did things come from and who did it) and annotations (who said what). orcid.org/0000-0001-9842-9718