Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale

Horton, Joshua T. and Boothroyd, Simon and Wagner, Jeffrey and Mitchell, Joshua A. and Gokey, Trevor and Dotson, David L. and Behara, Pavan Kumar and Ramaswamy, Venkata Krishnan and Mackey, Mark and Chodera, John D. and Anwar, Jamshed and Mobley, David L. and Cole, Daniel J. (2022) Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale. Journal of Chemical Information and Modeling. pp. 5622-5633. ISSN 1549-9596

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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 0.56 to 0.42 kcal/mol and correlation improved from 0.72 to 0.93 ).

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Journal Article
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Journal of Chemical Information and Modeling
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29 Nov 2022 12:45
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29 Nov 2022 12:45