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Structural and Functional Characterization of G Protein-Coupled Receptors with Deep Mutational Scanning

Eric M. Jones, View ORCID ProfileNathan B. Lubock, View ORCID ProfileAJ Venkatakrishnan, Jeffrey Wang, Alex M. Tseng, View ORCID ProfileJoseph M. Paggi, View ORCID ProfileNaomi R. Latorraca, Daniel Cancilla, Megan Satyadi, Jessica E. Davis, View ORCID ProfileM. Madan Babu, View ORCID ProfileRon O. Dror, View ORCID ProfileSriram Kosuri
doi: https://doi.org/10.1101/623108
Eric M. Jones
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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Nathan B. Lubock
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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AJ Venkatakrishnan
2MRC Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, UK
3Department of Computer Science, Stanford University, Stanford, CA 94305, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Jeffrey Wang
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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Alex M. Tseng
3Department of Computer Science, Stanford University, Stanford, CA 94305, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Joseph M. Paggi
3Department of Computer Science, Stanford University, Stanford, CA 94305, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Naomi R. Latorraca
3Department of Computer Science, Stanford University, Stanford, CA 94305, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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Daniel Cancilla
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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Megan Satyadi
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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Jessica E. Davis
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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M. Madan Babu
2MRC Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, UK
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Ron O. Dror
3Department of Computer Science, Stanford University, Stanford, CA 94305, Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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  • For correspondence: sri@ucla.edu ron.dror@stanford.edu
Sriram Kosuri
1Department of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA
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  • For correspondence: sri@ucla.edu ron.dror@stanford.edu
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Abstract

In humans, the 813 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.

Footnotes

  • This version adds some control experiments for individual verification, adjusts several figures for clarity, and adjusts the text to improve clarity and add statistical tests.

  • https://github.com/KosuriLab/b2-dms

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 04, 2020.
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Structural and Functional Characterization of G Protein-Coupled Receptors with Deep Mutational Scanning
Eric M. Jones, Nathan B. Lubock, AJ Venkatakrishnan, Jeffrey Wang, Alex M. Tseng, Joseph M. Paggi, Naomi R. Latorraca, Daniel Cancilla, Megan Satyadi, Jessica E. Davis, M. Madan Babu, Ron O. Dror, Sriram Kosuri
bioRxiv 623108; doi: https://doi.org/10.1101/623108
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Structural and Functional Characterization of G Protein-Coupled Receptors with Deep Mutational Scanning
Eric M. Jones, Nathan B. Lubock, AJ Venkatakrishnan, Jeffrey Wang, Alex M. Tseng, Joseph M. Paggi, Naomi R. Latorraca, Daniel Cancilla, Megan Satyadi, Jessica E. Davis, M. Madan Babu, Ron O. Dror, Sriram Kosuri
bioRxiv 623108; doi: https://doi.org/10.1101/623108

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