Direct-coupling analysis of residue co-evolution captures native contacts across many protein families

TL;DR

This paper demonstrates that Direct Coupling Analysis (DCA) effectively predicts residue contacts in proteins from sequence data, capturing native contacts and structural features across many protein families, aiding structural and functional predictions.

Contribution

The authors develop an efficient implementation of DCA that accurately predicts residue contacts and reveals structural signals beyond intra-domain contacts in large protein datasets.

Findings

DCA predicts a large number of correct residue contacts.

DCA captures signals related to protein conformations and interactions.

Predictions can guide de novo protein structure and complex formation modeling.

Abstract

The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting correlations among amino acid compositions at different sequence positions can be exploited to infer spatial contacts within the tertiary protein structure. Crucial to this inference is the ability to disentangle direct and indirect correlations, as accomplished by the recently introduced Direct Coupling Analysis (DCA) (Weigt et al. (2009) Proc Natl Acad Sci 106:67). Here we develop a computationally efficient implementation of DCA, which allows us to evaluate the accuracy of contact prediction by DCA for a large number of protein domains, based purely on sequence information. DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global structure of the contact map for the majority of the protein domains examined. Furthermore, our analysis captures clear signals beyond intra- domain residue contacts, arising, e.g., from alternative protein conformations, ligand- mediated residue couplings, and inter-domain interactions in protein oligomers. Our findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, provided the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.