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The similarity in the three-dimensional structures of homologous proteinsimposes strong constraints on their sequence variability. It has long beensuggested that the resulting correlations among amino acid compositions atdifferent sequence positions can be exploited to infer spatial contacts withinthe tertiary protein structure. Crucial to this inference is the ability todisentangle direct and indirect correlations, as accomplished by the recentlyintroduced Direct Coupling Analysis (DCA) (Weigt et al. (2009) Proc Natl AcadSci 106:67). Here we develop a computationally efficient implementation of DCA,which allows us to evaluate the accuracy of contact prediction by DCA for alarge number of protein domains, based purely on sequence information. DCA isshown to yield a large number of correctly predicted contacts, recapitulatingthe global structure of the contact map for the majority of the protein domainsexamined. Furthermore, our analysis captures clear signals beyond intra- domainresidue contacts, arising, e.g., from alternative protein conformations,ligand- mediated residue couplings, and inter-domain interactions in proteinoligomers. Our findings suggest that contacts predicted by DCA can be used as areliable guide to facilitate computational predictions of alternative proteinconformations, protein complex formation, and even the de novo prediction ofprotein domain structures, provided the existence of a large number ofhomologous sequences which are being rapidly made available due to advances ingenome sequencing.

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