A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model

2021/01/22 by Jaehyeok Jin, Yining Han, Alexander J. Pak +1 · 38 citations
Biochemistry, Genetics and Molecular Biology · Chemistry · Materials Science · Mathematics · Physics and Astronomy · #Artificial intelligence #Block Copolymer Self-Assembly #Chemistry #Computational chemistry #Computer science #Fidelity #Granularity #Leverage (statistics) #Mathematical optimization #Mathematics #Molecular dynamics #Pairwise comparison #Physics #Protein Structure and Dynamics #Statistical physics #Theoretical and Computational Physics #Water model

paper · open access · doi:10.1063/5.0026651

published in The Journal of Chemical Physics 154(4), 044104 (American Institute of Physics)

openalex publication_date 2021/01/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Water is undoubtedly one of the most important molecules for a variety of chemical and physical systems, and constructing precise yet effective coarse-grained (CG) water models has been a high priority for computer simulations. To recapitulate important local correlations in the CG water model, explicit higher-order interactions are often included. However, the advantages of coarse-graining may then be offset by the larger computational cost in the model parameterization and simulation execution. To leverage both the computational efficiency of the CG simulation and the inclusion of higher-order interactions, we propose a new statistical mechanical theory that effectively projects many-body interactions onto pairwise basis sets. The many-body projection theory presented in this work shares similar physics from liquid state theory, providing an efficient approach to account for higher-order interactions within the reduced model. We apply this theory to project the widely used Stillinger-Weber three-body interaction onto a pairwise (two-body) interaction for water. Based on the projected interaction with the correct long-range behavior, we denote the new CG water model as the Bottom-Up Many-Body Projected Water (BUMPer) model, where the resultant CG interaction corresponds to a prior model, the iteratively force-matched model. Unlike other pairwise CG models, BUMPer provides high-fidelity recapitulation of pair correlation functions and three-body distributions, as well as N-body correlation functions. BUMPer extensively improves upon the existing bottom-up CG water models by extending the accuracy and applicability of such models while maintaining a reduced computational cost.

Citations

• On Information and Sufficiency
• Flexible simple point-charge water model with improved liquid-state properties
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• The multiscale coarse-graining method. VI. Implementation of three-body coarse-grained potentials
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• Perspective: Coarse-grained models for biomolecular systems
• The missing term in effective pair potentials
• The relative entropy is fundamental to multiscale and inverse thermodynamic problems
• Multiscale coarse graining of liquid-state systems
• Coarse-graining errors and numerical optimization using a relative entropy framework
• Molecular dynamics simulations at constant pressure and/or temperature

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• Bottom-up Coarse-Graining: Principles and Perspectives. [europepmc]
• Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models through Virtual Particles. [europepmc]
• OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining. [europepmc]
• Coarse-Graining with Equivariant Neural Networks: A Path Toward Accurate and Data-Efficient Models. [europepmc]
• Density- and Temperature-Dependent Potentials: Redefinition of the Local Density to Improve the Simulation of Liquids within Generalized Dissipative Particle Dynamics. [europepmc]
• Mapping Still Matters: Coarse-Graining with Machine Learning Potentials. [europepmc]

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