Coevolution-based inference of amino acid interactions underlying protein function
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
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Data from: The role of feeding morphology and competition in governing the diet breadth of sympatric stomatopod crustaceans| Available at Dryad Digital Repository under a CC0 Public Domain Dedication.
Article and author information
Author details
Funding
National Institutes of Health (RO1GM123456)
- Rama Ranganathan
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
- Nir Ben-Tal, Tel Aviv University, Israel
Version history
- Received: December 12, 2017
- Accepted: July 18, 2018
- Accepted Manuscript published: July 19, 2018 (version 1)
- Accepted Manuscript updated: July 20, 2018 (version 2)
- Version of Record published: August 30, 2018 (version 3)
Copyright
© 2018, Salinas & Ranganathan
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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