ArticleThe journal of physical chemistry. B2024
Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields.
Article in The journal of physical chemistry. B, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Developing and Benchmarking Sage 2.3.0 with the AshGC Neural Network Charge Model.Journal of chemical theory and computation · 2026Article
- Ensemble Sensitivity to Chemical Modifications in Free and Bound Macrocyclic Peptides.The journal of physical chemistry. B · 2026Article
- Toward Improving Multiple Time Step QM/MM Simulations with Δ-Machine Learning.The journal of physical chemistry. B · 2025Article
- Inhibition of human N myristoyltransferase 1 as a strategy to suppress cancer progression driven by myristoylation.Scientific reports · 2025Article
- MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules.Journal of the American Chemical Society · 2025Article
- Data-driven parametrization of molecular mechanics force fields for expansive chemical space coverage.Chemical science · 2025Article
- A Comparison of the Electronic Properties of Selected Antioxidants Vitamin C, Uric Acid, NAC and Melatonin with Guanosine Derivatives: A Theoretical Study.Molecules (Basel, Switzerland) · 2024Article
- The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.The journal of physical chemistry. B · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
A wide range of density functional methods and basis sets are available to derive the electronic structure and properties of molecules. Quantum mechanical calculations are too computationally intensive for routine simulation of molecules in the condensed phase, prompting the development of computationally efficient force fields based on quantum mechanical data. Parametrizing general force fields, which cover a vast chemical space, necessitates the generation of sizable quantum mechanical data sets with optimized geometries and torsion scans. To achieve this efficiently, choosing a quantum mechanical method that balances computational cost and accuracy is crucial. In this study, we seek to assess the accuracy of quantum mechanical theory for specific properties such as conformer energies and torsion energetics. To comprehensively evaluate various methods, we focus on a representative set of 59 diverse small molecules, comparing approximately 25 combinations of functional and basis sets against the reference level coupled cluster calculations at the complete basis set limit.
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Registered trials
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