Published July 19, 2018 | Version v1
Journal article Open

Coevolution-based inference of amino acid interactions underlying protein function

  • 1. UT Southwestern Medical Center
  • 2. University of Chicago

Description

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:

Salinas VHRanganathan R (2017) Data from: Inferring amino acid interactions underlying protein function Available at Dryad Digital Repository under a CC0 Public Domain Dedication. http://dx.doi.org/10.5061/dryad.gk4m1

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Additional details

Identifiers

DOI
10.7554/eLife.34300
Other
oai:uchicago.tind.io:9950

Funding

Welch Foundation
I-1366
National Institutes of Health
RO1GM12345

UChicago Information

Division(s)
Biological Sciences Division, Pritzker School of Molecular Engineering
Department(s)
Biochemistry and Molecular Biology
Center(s) or Institute(s)
Center for the Physics of Evolving Systems