Coevolution-based inference of amino acid interactions underlying protein function

  1. Victor H Salinas
  2. Rama Ranganathan  Is a corresponding author
  1. University of Texas Southwestern Medical Center, United States
  2. The University of Chicago, United States

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. 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.
  2. Rama Ranganathan

    Center for Physics of Evolving Systems, Biochemistry and Molecular Biology, The University of Chicago, 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

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

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

Version 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, 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.

Metrics

  • 10,084
    views
  • 1,376
    downloads
  • 104
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Victor H Salinas
  2. Rama Ranganathan
(2018)
Coevolution-based inference of amino acid interactions underlying protein function
eLife 7:e34300.
https://doi.org/10.7554/eLife.34300

Share this article

https://doi.org/10.7554/eLife.34300

Further reading

    1. Biochemistry and Chemical Biology
    2. Neuroscience
    Katarzyna Marta Zoltowska, Utpal Das ... Lucía Chávez-Gutiérrez
    Research Article

    Amyloid β (Aβ) peptides accumulating in the brain are proposed to trigger Alzheimer’s disease (AD). However, molecular cascades underlying their toxicity are poorly defined. Here, we explored a novel hypothesis for Aβ42 toxicity that arises from its proven affinity for γ-secretases. We hypothesized that the reported increases in Aβ42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on γ-secretases, and thereby impair downstream signaling events. We conducted kinetic analyses of γ-secretase activity in cell-free systems in the presence of Aβ, as well as cell-based and ex vivo assays in neuronal cell lines, neurons, and brain synaptosomes to assess the impact of Aβ on γ-secretases. We show that human Aβ42 peptides, but neither murine Aβ42 nor human Aβ17–42 (p3), inhibit γ-secretases and trigger accumulation of unprocessed substrates in neurons, including C-terminal fragments (CTFs) of APP, p75, and pan-cadherin. Moreover, Aβ42 treatment dysregulated cellular homeostasis, as shown by the induction of p75-dependent neuronal death in two distinct cellular systems. Our findings raise the possibility that pathological elevations in Aβ42 contribute to cellular toxicity via the γ-secretase inhibition, and provide a novel conceptual framework to address Aβ toxicity in the context of γ-secretase-dependent homeostatic signaling.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Ya-Juan Wang, Xiao-Jing Di ... Ting-Wei Mu
    Research Article Updated

    Protein homeostasis (proteostasis) deficiency is an important contributing factor to neurological and metabolic diseases. However, how the proteostasis network orchestrates the folding and assembly of multi-subunit membrane proteins is poorly understood. Previous proteomics studies identified Hsp47 (Gene: SERPINH1), a heat shock protein in the endoplasmic reticulum lumen, as the most enriched interacting chaperone for gamma-aminobutyric acid type A (GABAA) receptors. Here, we show that Hsp47 enhances the functional surface expression of GABAA receptors in rat neurons and human HEK293T cells. Furthermore, molecular mechanism study demonstrates that Hsp47 acts after BiP (Gene: HSPA5) and preferentially binds the folded conformation of GABAA receptors without inducing the unfolded protein response in HEK293T cells. Therefore, Hsp47 promotes the subunit-subunit interaction, the receptor assembly process, and the anterograde trafficking of GABAA receptors. Overexpressing Hsp47 is sufficient to correct the surface expression and function of epilepsy-associated GABAA receptor variants in HEK293T cells. Hsp47 also promotes the surface trafficking of other Cys-loop receptors, including nicotinic acetylcholine receptors and serotonin type 3 receptors in HEK293T cells. Therefore, in addition to its known function as a collagen chaperone, this work establishes that Hsp47 plays a critical and general role in the maturation of multi-subunit Cys-loop neuroreceptors.