Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why

Xie, Pinchen; E, Weinan

doi:10.1021/acs.jctc.4c00729

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Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why

Xie, Pinchen·E, Weinan

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Abstract

A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained (CG) conformational dynamics. Constrained by the fluctuation–dissipation theorem, the approach can build CG models in dynamical consistency (DC) with all-atom molecular dynamics. Here, we also propose practical criteria for AIGLE to enforce long-term DC. Case studies of a toy polymer, with 20 CG sites, and the alanine dipeptide, with two dihedral angles, elucidate why one should adopt AIGLE or its Markovian limit for modeling CG conformational dynamics in practice.

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS Circuits Computational chemistry Diffusion Langevin equation (AIGLE)Markov modeling Polymers

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Xie, Pinchen, E, Weinan. 2024-09-11. Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why. https://doi.org/10.1021/acs.jctc.4c00729

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