Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information

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Cite this article as: eLife 2014;3:e02030 doi: 10.7554/eLife.02030

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Abstract

Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood based method to covary across protein-protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex provided that the number of aligned sequences is greater than the average of the lengths of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic (TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.

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Author details

Sergey Ovchinnikov

Howard Hughes Medical Institute, University of Washington, Seattle, United States

Competing interests
The authors declare that no competing interests exist.
Hetunandan Kamisetty

Howard Hughes Medical Institute, University of Washington, Seattle, United States

Competing interests
The authors declare that no competing interests exist.
David Baker

Howard Hughes Medical Institute, University of Washington, Seattle, United States

For correspondence
dabaker@u.washington.edu

Competing interests
The authors declare that no competing interests exist.

Reviewing Editor

Benoit Roux, University of Chicago, United States

Publication history

Received: December 8, 2013
Accepted: April 22, 2014
Accepted Manuscript published: May 1, 2014 (version 1)
Version of Record published: May 27, 2014 (version 2)

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This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.