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

Eric M. Jones(Broad Center), Nathan B. Lubock(Broad Center), AJ Venkatakrishnan(MRC Laboratory of Molecular Biology), Jeffrey Wang(Broad Center), Alex M. Tseng(Stanford University), Joseph M. Paggi(Stanford University), Naomi R. Latorraca(Stanford University), Daniel Cancilla(Broad Center), Megan Satyadi(Broad Center), Jessica E. Davis(Broad Center), M. Madan Babu(MRC Laboratory of Molecular Biology), Ron O. Dror(Stanford University), Sriram Kosuri(Broad Center)
eLife
October 21, 2020
Cited by 174Open Access
Full Text

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.


Related Papers

No related papers found

Powered by citation graph analysis