Structural and functional characterization of G protein-coupled receptors with deep mutational scanning

  1. Eric M Jones
  2. Nathan B Lubock
  3. A J Venkatakrishnan
  4. Jeffrey Wang
  5. Alex M Tseng
  6. Joseph M Paggi
  7. Naomi R Latorraca
  8. Daniel Cancilla
  9. Megan Satyadi
  10. Jessica E Davis
  11. M Madan Babu
  12. Ron O Dror  Is a corresponding author
  13. Sriram Kosuri  Is a corresponding author
  1. University of California, Los Angeles, United States
  2. Stanford University, United States
  3. MRC Laboratory of Molecular Biology, United Kingdom

Abstract

In humans, the >800 G protein-coupled receptors (GPCRs) are responsible for transducing diverse chemical stimuli to alter cell state, and are the largest class of drug targets. Their myriad structural conformations and various modes of signaling make it challenging to understand their structure and function. Here we developed a platform to characterize large libraries of GPCR variants in human cell lines with a barcoded transcriptional reporter of G-protein signal transduction. We tested 7,800 of 7,828 possible single amino acid substitutions to the beta-2 adrenergic receptor (β2AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for β2AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we resolve residues critical for signaling, including all major structural motifs and molecular interfaces. We also find a previously uncharacterized structural latch spanning the first two extracellular loops that is highly conserved across Class A GPCRs and is conformationally rigid in both the inactive and active states of the receptor. More broadly, by linking deep mutational scanning with engineered transcriptional reporters, we establish a generalizable method for exploring pharmacogenomics, structure and function across broad classes of drug receptors.

Data availability

Sequencing data have been submitted to GEO and the accession code is GSE144819.

The following data sets were generated

Article and author information

Author details

  1. Eric M Jones

    Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center o, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    Eric M Jones, holds equity and is employed by Octant, Inc., a company to which patent rights based on this work have been licensed (Application No. 62/528,833).
  2. Nathan B Lubock

    Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    Nathan B Lubock, Employed by and holds equity in Octant Inc. to which patent rights based on this work have been licensed (Application No. 62/528,833).
  3. A J Venkatakrishnan

    Department of Computer Science, Institute for Computational and Mathematical Engineering, Department of Molecular and Cellular Physiology, Department of Structural Biology, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2819-3214
  4. Jeffrey Wang

    Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center o, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  5. Alex M Tseng

    Department of Computer Science, Institute for Computational and Mathematical Engineering, Department of Molecular and Cellular Physiology, Department of Structural Biology, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  6. Joseph M Paggi

    Department of Computer Science, Institute for Computational and Mathematical Engineering, Department of Molecular and Cellular Physiology, Department of Structural Biology, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  7. Naomi R Latorraca

    Biophysics Program, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  8. Daniel Cancilla

    Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center o, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  9. Megan Satyadi

    Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center o, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  10. Jessica E Davis

    Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  11. M Madan Babu

    MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
    Competing interests
    No competing interests declared.
  12. Ron O Dror

    Biophysics Program, Stanford University, Stanford, United States
    For correspondence
    ron.dror@stanford.edu
    Competing interests
    No competing interests declared.
  13. Sriram Kosuri

    Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, United States
    For correspondence
    sri@ucla.edu
    Competing interests
    Sriram Kosuri, holds equity and is employed by Octant, Inc., a company to which patent rights based on this work have been licensed to (Application No. 62/528,833).
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4661-0600

Funding

National Science Foundation (1556207)

  • Sriram Kosuri

National Institutes of Health (GM007185)

  • Sriram Kosuri

National Institutes of Health (5T32GM008496)

  • Sriram Kosuri

National Institutes of Health (DP2GM114829)

  • Sriram Kosuri

Medical Research Council (MC_U105185859)

  • Sriram Kosuri

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Dan Larhammar, Uppsala University, Sweden

Version history

  1. Received: January 5, 2020
  2. Accepted: October 16, 2020
  3. Accepted Manuscript published: October 21, 2020 (version 1)
  4. Version of Record published: December 1, 2020 (version 2)

Copyright

© 2020, Jones et al.

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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  1. Eric M Jones
  2. Nathan B Lubock
  3. A J Venkatakrishnan
  4. Jeffrey Wang
  5. Alex M Tseng
  6. Joseph M Paggi
  7. Naomi R Latorraca
  8. Daniel Cancilla
  9. Megan Satyadi
  10. Jessica E Davis
  11. M Madan Babu
  12. Ron O Dror
  13. Sriram Kosuri
(2020)
Structural and functional characterization of G protein-coupled receptors with deep mutational scanning
eLife 9:e54895.
https://doi.org/10.7554/eLife.54895

Share this article

https://doi.org/10.7554/eLife.54895

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