ArticleJournal of chemical information and modeling2022
Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.
Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Training a force field for proteins and small molecules from scratch.Chemical science · 2026Article
- Large-Scale Collaborative Assessment of Binding Free Energy Calculations for Drug Discovery Using OpenFE.Journal of chemical information and modeling · 2026Article
- Fast Fourier Transform Enables Automated Parametrization of Complex Dihedral Potentials in All-Atom and Coarse-Grained Force Fields.Journal of chemical information and modeling · 2026Article
- Benchmarking OPLS-AA and OpenFF for HDI-PEG Thermoplastic Polyurethanes with Varying Soft-Segment Length.Molecules (Basel, Switzerland) · 2026Article
- Automated Force Field Developer and Optimizer Platform: Torsion Reparameterization.Journal of chemical information and modeling · 2026Article
- The Open Molecular Software Foundation (OMSF) and the Growing Role of Open Source Software in Molecular Modeling.Journal of chemical information and modeling · 2026Review
- Computing Solvation Free Energies of Small Molecules with Experimental Accuracy.Journal of the American Chemical Society · 2026Article
- HessFit: Deriving Molecule-Specific Force Fields from Quantum Mechanical Hessians.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Unraveling Torsional Preferences: Comparative Analysis of Torsion Motif Torsional-Angle Distributions across Different Environments.Journal of chemical information and modeling · 2025Article
- A Graph Neural Network Charge Model Targeting Accurate Electrostatic Properties of Organic Molecules.Journal of chemical theory and computation · 2025Article
- Atomistic Polymer Modeling: Recent Advances and Challenges in Building and Parametrization Workflows.Macromolecules · 2025Review
- Speed up Multi-Scale Force-Field Parameter Optimization by Substituting Molecular Dynamics Calculations with a Machine Learning Surrogate Model.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- A Simple, Polarizable, Rigid, 3-Point Water Model Using the Direct Polarization Approximation.Journal of chemical theory and computation · 2025Article
- Application of Free Energy Perturbation (FEP) Methodology for Predicting the Binding Affinity of Macrocyclic JAK2 Inhibitor Analogues of Pacritinib.ACS medicinal chemistry letters · 2025Article
- TrIP2: Expanding the Transformer Interatomic Potential Demonstrates Architectural Scalability for Organic Compounds.The journal of physical chemistry. A · 2025Article
- MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules.Journal of the American Chemical Society · 2025Article
- Expanded ensemble predictions of toluene-water partition coefficients in the SAMPL9 logPhysical chemistry chemical physics : PCCP · 2025Article
- Data-driven parametrization of molecular mechanics force fields for expansive chemical space coverage.Chemical science · 2025Article
- CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.The journal of physical chemistry. B · 2024Review
- Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields.The journal of physical chemistry. B · 2024Article
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Authors and funding
13 authors.
Funding
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 0.56
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.