Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.

ABSTRACT: Accurate force fields are crucial for molecular dynamics investigation of complex biological systems. Building accurate protein force fields from quantum mechanical (QM) calculations is challenging due to the complexity of proteins and high computational costs of QM methods. In order to overcome these two difficulties, here we developed the residue-based systematic molecular fragmentation method to partition general proteins into only 20 types of amino acid dipeptides and one type of peptide bond at level 1. The total energy of proteins is the combination of the energies of these fragments. Each type of the fragments is then parametrized using neural network (NN) representation of the QM reference. Adopting NN representation can circumvent the limitation of the analytic form of classical m

SUBMITTER: Wang H 

PROVIDER: S-EPMC6372335 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature