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Cited by 168Receptor Mechanisms and SignalingNeuroscience and Neuropharmacology ResearchProtein Kinase Regulation and GTPase Signaling

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

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Jones, Eric M, Lubock, Nathan B, Venkatakrishnan, AJ, Wang, Jeffrey, Tseng, Alex M, Paggi, Joseph M, Latorraca, Naomi R, Cancilla, Daniel +5 more·2020·eLife
DOI 10.7554/elife.54895PMC PMC7707821

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Abstract

The >800 human 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 7800 of 7828 possible single amino acid substitutions to the beta-2 adrenergic receptor (β 2 AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for β 2 AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we identify 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.

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Authors
Jones, E. M., Lubock, N. B., Venkatakrishnan, A., Wang, J., Tseng, A. M., Paggi, J. M., Latorraca, N. R., Cancilla, D., Satyadi, M., Davis, J. E., Babu, M. M., Dror, R. O., & Kosuri, S.
Affiliations
  • University of California, Los Angeles (US)
  • MRC Laboratory of Molecular Biology (GB)
  • Stanford Medicine (US)
Corresponding author
  • Dror, Ron O
  • Kosuri, Sriram
ORCID
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2020-10-21
Volume
9
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.54895
PMC
PMC7707821
OpenAlex
W3094232626
Cited by
168
References
9
Citations by year
2026: 40 · 2025: 24 · 2024: 26 · 2023: 29 · 2022: 22 · 2021: 20 · 2020: 5 · 2019: 2
FWCI
6.17
Type
journal article
Language
en
Open access
Licence
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Science Foundation (1556207)
  • National Institutes of Health (GM007185, 5T32GM008496, DP2GM114829, GM127359)
  • Medical Research Council (MC_U105185859)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
Keywords
G protein-coupled receptors, deep mutational scanning, beta2-adrenergic receptor, G protein signaling, transcriptional reporter, single amino acid substitution, loss-of-function mutations, basal receptor activity, class A GPCRs, pharmacogenomics, unsupervised learning, receptor structure-function
MeSH terms
Machine Learning, Gene Editing, Cloning, Molecular, DNA Mutational Analysis, Humans, Models, Molecular, Protein Conformation, Receptors, G-Protein-Coupled, HEK293 Cells, DNA Barcoding, Taxonomic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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