ArticleJournal of chemical theory and computation2022
Improving Force Field Accuracy by Training against Condensed-Phase Mixture Properties.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- GOPAL: A Water Model with Improved Thermodynamic Properties over a Large Pressure and Temperature Range Optimized Using Multistate Reweighting and Configuration Space Mapping.Journal of chemical theory and computation · 2025Article
- A Simple, Polarizable, Rigid, 3-Point Water Model Using the Direct Polarization Approximation.Journal of chemical theory and computation · 2025Article
- Fine-tuning molecular mechanics force fields to experimental free energy measurements.bioRxiv : the preprint server for biology · 2025Article
- Machine-learned molecular mechanics force fields from large-scale quantum chemical data.Chemical science · 2024Article
- The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.The journal of physical chemistry. B · 2024Article
- Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields.The journal of physical chemistry. B · 2024Article
- 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
- Using physical property surrogate models to perform accelerated multi-fidelity optimization of force field parameters.Digital discovery · 2023Article
- Regularized by Physics: Graph Neural Network Parametrized Potentials for the Description of Intermolecular Interactions.Journal of chemical theory and computation · 2023Article
- Open Force Field Evaluator: An Automated, Efficient, and Scalable Framework for the Estimation of Physical Properties from Molecular Simulation.Journal of chemical theory and computation · 2022Article
- Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields.Communications chemistry · 2022Review
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6 authors.
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Abstract
Developing a sufficiently accurate classical force field representation of molecules is key to realizing the full potential of molecular simulations as a route to gaining a fundamental insight into a broad spectrum of chemical and biological phenomena. This is only possible, however, if the many complex interactions between molecules of different species in the system are accurately captured by the model. Historically, the intermolecular van der Waals (vdW) interactions have primarily been trained against densities and enthalpies of vaporization of pure (single-component) systems, with occasional usage of hydration free energies. In this study, we demonstrate how including physical property data of binary mixtures can better inform these parameters, encoding more information about the underlying physics of the system in complex chemical mixtures. To demonstrate this, we retrain a select number of Lennard-Jones parameters describing the vdW interactions of the OpenFF 1.0.0 (Parsley) fixed charge force field against training sets composed of densities and enthalpies of mixing for binary liquid mixtures as well as densities and enthalpies of vaporization of pure liquid systems and assess the performance of each of these combinations. We show that retraining against the mixture data improves the force field's ability to reproduce mixture properties, including solvation free energies, correcting some systematic errors that exist when training vdW interactions against properties of pure systems only.
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