1. Biochemistry and Chemical Biology
  2. Computational and Systems Biology
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Coevolution-based inference of amino acid interactions underlying protein function

  1. Rama Ranganathan  Is a corresponding author
  2. Victor H Salinas
  1. University of Texas Southwestern Medical Center, United States
Research Article
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Cite this article as: eLife 2018;7:e34300 doi: 10.7554/eLife.34300

Abstract

Protein function arises from a poorly understood pattern of energetic interactions between amino acid residues. Sequence-based strategies for deducing this pattern have been proposed, but lack of benchmark data has limited experimental verification. Here, we extend deep-mutation technologies to enable measurement of many thousands of pairwise amino acid couplings in several homologs of a protein family - a deep coupling scan (DCS). The data show that cooperative interactions between residues are loaded in a sparse, evolutionarily conserved, spatially contiguous network of amino acids. The pattern of amino acid coupling is quantitatively captured in the coevolution of amino acid positions, especially as indicated by the statistical coupling analysis (SCA), providing experimental confirmation of the key tenets of this method. This work exposes the collective nature of physical constraints on protein function and clarifies its link with sequence analysis, enabling a general practical approach for understanding the structural basis for protein function.

Data availability

Mutation data have been deposited in the Dryad database under accession code doi:10.5061/dryad.gk4m1

The following data sets were generated

Article and author information

Author details

  1. Rama Ranganathan

    Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    ranganathanr@uchicago.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5463-8956
  2. Victor H Salinas

    Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (RO1GM123456)

  • Victor H Salinas

Welch Foundation (I-1366)

  • Rama Ranganathan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Nir Ben-Tal, Tel Aviv University, Israel

Publication history

  1. Received: December 12, 2017
  2. Accepted: July 18, 2018
  3. Accepted Manuscript published: July 19, 2018 (version 1)
  4. Accepted Manuscript updated: July 20, 2018 (version 2)
  5. Version of Record published: August 30, 2018 (version 3)

Copyright

© 2018, Ranganathan & Salinas

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

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