Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.

ABSTRACT: A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically

SUBMITTER: Illarionov A 

PROVIDER: S-EPMC10623557 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature