ArticleJournal of chemical information and modeling2022
Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field.
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 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Deep residual learning for molecular force fields.Nature communications · 2026Article
- Large-Scale Collaborative Assessment of Binding Free Energy Calculations for Drug Discovery Using OpenFE.Journal of chemical information and modeling · 2026Article
- Developing and Benchmarking Sage 2.3.0 with the AshGC Neural Network Charge Model.Journal of chemical theory and computation · 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
- Quantum Chemistry in Drug Design: Applications, Challenges, and the Need for Speed.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Condensation of Force Field Parameters from Machine Learning Predicted Distributions for High-Throughput Virtual Screening Applications.Journal of chemical information and modeling · 2025Article
- Beyond Barriers, Big Crystallization Hurdles: Atropisomerism in Beyond Rule of Five Compounds Explored by Computational and NMR Studies.Molecular pharmaceutics · 2025Article
- Data-driven parametrization of molecular mechanics force fields for expansive chemical space coverage.Chemical science · 2025Article
- Machine-learned molecular mechanics force fields from large-scale quantum chemical data.Chemical science · 2024Article
- The Art and Science of Molecular Docking.Annual review of biochemistry · 2024Review
- The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.The journal of physical chemistry. B · 2024Article
- Distribution of Bound Conformations in Conformational Ensembles for X-ray Ligands Predicted by the ANI-2X Machine Learning Potential.Journal of chemical information and modeling · 2023Article
- Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness.Journal of chemical theory and computation · 2023Review
- A transferable double exponential potential for condensed phase simulations of small molecules.Digital discovery · 2023Article
- Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field.Journal of chemical theory and computation · 2023Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.
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Registered trials
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.