QMEANDisCo—distance constraints applied on model quality estimation

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…

• SI
  Swiss Institute of Bioinformatics