QMEANDisCo-distance constraints applied on model quality estimation.

ABSTRACT:

Motivation

Methods that estimate the quality of a 3D protein structure model in absence of an experimental reference structure are crucial to determine a model's utility and potential applications. Single model methods assess individual models whereas consensus methods require an ensemble of models as input. In this work, we extend the single model composite score QMEAN that employs statistical potentials of mean force and agreement terms by introducing a consensus-based distance constraint (DisCo) score.

Results

DisCo exploits distance distributions from experimentally determined protein structures that are homologous to the model being assessed. Feed-forward neural networks are trained to adaptively weigh contributions by the multi-template DisCo score and classical single

SUBMITTER: Studer G 

PROVIDER: S-EPMC7075525 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature