Thermodynamic Transferability in Coarse-Grained Force Fields Using Graph Neural Networks.

ABSTRACT: Coarse-graining is a molecular modeling technique in which an atomistic system is represented in a simplified fashion that retains the most significant system features that contribute to a target output while removing the degrees of freedom that are less relevant. This reduction in model complexity allows coarse-grained molecular simulations to reach increased spatial and temporal scales compared with corresponding all-atom models. A core challenge in coarse-graining is to construct a force field that represents the interactions in the new representation in a way that preserves the atomistic-level properties. Many approaches to building coarse-grained force fields have limited transferability between different thermodynamic conditions as a result of averaging over internal fluctuations at

SUBMITTER: Shinkle E 

PROVIDER: S-EPMC11635977 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature