Structure-based network analysis of an evolved G protein-coupled receptor homodimer interface

Authors

  • Sara E. Nichols,

    Corresponding author
    1. Department of Pharmacology, University of California, San Diego, La Jolla, California
    2. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California
    • Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California
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    • Sara E. Nichols and Carlos X. Hernández contributed equally to this work.

  • Carlos X. Hernández,

    1. Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California
    2. Department of Applied Mathematics, Columbia University, New York, New York
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    • Sara E. Nichols and Carlos X. Hernández contributed equally to this work.

  • Yi Wang,

    1. Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California
    2. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California
    3. Department of Physics, The Chinese University of Hong Kong, Hong Kong
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  • James Andrew McCammon

    1. Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California
    2. Department of Pharmacology, University of California, San Diego, La Jolla, California
    3. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California
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Correspondence to: Sara E. Nichols, Howard Hughes Medical Institute, University of California, San Diego, 9500 Gilman Dr., M/C 0365, La Jolla, CA 92093-0365. E-mail: senichols@ucsd.edu

Abstract

Crystallographic structures and experimental assays of human CXC chemokine receptor type 4 (CXCR4) provide strong evidence for the capacity to homodimerize, potentially as a means of allosteric regulation. Even so, how this homodimer forms and its biological significance has yet to be fully characterized. By applying principles from network analysis, sequence-based approaches such as statistical coupling analysis to determine coevolutionary residues, can be used in conjunction with molecular dynamics simulations to identify residues relevant to dimerization. Here, the predominant coevolution sector lies along the observed dimer interface, suggesting functional relevance. Furthermore, coevolution scoring provides a basis for determining significant nodes, termed hubs, in the network formed by residues found along the interface of the homodimer. These node residues coincide with hotspots indicating potential druggability. Drug design efforts targeting such key residues could potentially result in modulation of binding and therapeutic benefits for disease states, such as lung cancers, lymphomas and latent HIV-1 infection. Furthermore, this method may be applied to any protein–protein interaction.

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