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

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.

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.

Metrics

  • 10,126
    views
  • 1,380
    downloads
  • 109
    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. Rama Ranganathan
  2. Victor H Salinas
(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
    Swarang Sachin Pundlik, Alok Barik ... Arvind Ramanathan
    Short Report

    Senescent cells are characterized by multiple features such as increased expression of senescence-associated β-galactosidase activity (SA β-gal) and cell cycle inhibitors such as p21 or p16. They accumulate with tissue damage and dysregulate tissue homeostasis. In the context of skeletal muscle, it is known that agents used for chemotherapy such as Doxorubicin (Doxo) cause buildup of senescent cells, leading to the inhibition of tissue regeneration. Senescent cells influence the neighboring cells via numerous secreted factors which form the senescence-associated secreted phenotype (SASP). Lipids are emerging as a key component of SASP that can control tissue homeostasis. Arachidonic acid-derived lipids have been shown to accumulate within senescent cells, specifically 15d-PGJ2, which is an electrophilic lipid produced by the non-enzymatic dehydration of the prostaglandin PGD2. This study shows that 15d-PGJ2 is also released by Doxo-induced senescent cells as an SASP factor. Treatment of skeletal muscle myoblasts with the conditioned medium from these senescent cells inhibits myoblast fusion during differentiation. Inhibition of L-PTGDS, the enzyme that synthesizes PGD2, diminishes the release of 15d-PGJ2 by senescent cells and restores muscle differentiation. We further show that this lipid post-translationally modifies Cys184 of HRas in C2C12 mouse skeletal myoblasts, causing a reduction in the localization of HRas to the Golgi, increased HRas binding to Ras Binding Domain (RBD) of RAF Kinase (RAF-RBD), and activation of cellular Mitogen Activated Protein (MAP) kinase–Extracellular Signal Regulated Kinase (Erk) signaling (but not the Akt signaling). Mutating C184 of HRas prevents the ability of 15d-PGJ2 to inhibit the differentiation of muscle cells and control the activity of HRas. This work shows that 15d-PGJ2 released from senescent cells could be targeted to restore muscle homeostasis after chemotherapy.

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Duk-Su Koh, Anastasiia Stratiievska ... Sharona E Gordon
    Tools and Resources

    Ligands such as insulin, epidermal growth factor, platelet-derived growth factor, and nerve growth factor (NGF) initiate signals at the cell membrane by binding to receptor tyrosine kinases (RTKs). Along with G-protein-coupled receptors, RTKs are the main platforms for transducing extracellular signals into intracellular signals. Studying RTK signaling has been a challenge, however, due to the multiple signaling pathways to which RTKs typically are coupled, including MAP/ERK, PLCγ, and Class 1A phosphoinositide 3-kinases (PI3K). The multi-pronged RTK signaling has been a barrier to isolating the effects of any one downstream pathway. Here, we used optogenetic activation of PI3K to decouple its activation from other RTK signaling pathways. In this context, we used genetic code expansion to introduce a click chemistry noncanonical amino acid into the extracellular side of membrane proteins. Applying a cell-impermeant click chemistry fluorophore allowed us to visualize delivery of membrane proteins to the plasma membrane in real time. Using these approaches, we demonstrate that activation of PI3K, without activating other pathways downstream of RTK signaling, is sufficient to traffic the TRPV1 ion channels and insulin receptors to the plasma membrane.