Open Force Field BespokeFit: Automating bespoke torsion parametrization at scale Journal Article


Authors: Horton, J. T.; Boothroyd, S.; Wagner, J.; Mitchell, J. A.; Gokey, T.; Dotson, D. L.; Behara, P. K.; Ramaswamy, V. K.; Mackey, M.; Chodera, J. D.; Anwar, J.; Mobley, D. L.; Cole, D. J.
Article Title: Open Force Field BespokeFit: Automating bespoke torsion parametrization at scale
Abstract: The development of accurate transferable force fields is key to realizing the full potential of atomistic modeling in the study of biological processes such as protein-ligand binding for drug discovery. State-of-the-art transferable force fields, such as those produced by the Open Force Field Initiative, use modern software engineering and automation techniques to yield accuracy improvements. However, force field torsion parameters, which must account for many stereoelectronic and steric effects, are considered to be less transferable than other force field parameters and are therefore often targets for bespoke parametrization. Here, we present the Open Force Field QCSubmit and BespokeFit software packages that, when combined, facilitate the fitting of torsion parameters to quantum mechanical reference data at scale. We demonstrate the use of QCSubmit for simplifying the process of creating and archiving large numbers of quantum chemical calculations, by generating a dataset of 671 torsion scans for druglike fragments. We use BespokeFit to derive individual torsion parameters for each of these molecules, thereby reducing the root-mean-square error in the potential energy surface from 1.1 kcal/mol, using the original transferable force field, to 0.4 kcal/mol using the bespoke version. Furthermore, we employ the bespoke force fields to compute the relative binding free energies of a congeneric series of inhibitors of the TYK2 protein, and demonstrate further improvements in accuracy, compared to the base force field (MUE reduced from 0.560.390.77 to 0.420.280.59 kcal/mol and R2 correlation improved from 0.720.350.87 to 0.930.840.97). © 2022 The Authors. Published by American Chemical Society.
Keywords: proteins; protein; protein binding; drug discovery; chemistry; ligand; ligands; binding energy; software; ligand binding; quantum theory; quantum chemistry; biological process; entropy; potential energy; state of the art; mean square error; torsional stress; large dataset; forcefields; atomistic modelling; engineering techniques; parametrizations; protein ligands; torsion parameters
Journal Title: Journal of Chemical Information and Modeling
Volume: 62
Issue: 22
ISSN: 1549-9596
Publisher: American Chemical Society  
Date Published: 2022-11-28
Start Page: 5622
End Page: 5633
Language: English
DOI: 10.1021/acs.jcim.2c01153
PUBMED: 36351167
PROVIDER: scopus
PMCID: PMC9709916
DOI/URL:
Notes: Article -- Export Date: 3 January 2023 -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. John Damon Chodera
    118 Chodera