Efficient experimental characterization of the GPCRome via deep receptor scanning

G protein-coupled receptors (GPCRs) mediate a variety of signaling pathways and represent the most common class of pharmaceutical target. While advances in structural biochemistry have provided deep functional insights into key receptors, many of the 800+ human GPCRs remain understudied. We introduce a versatile "deep receptor scanning" platform that can be used to experimentally characterize 766 human GPCRs and 174 known GPCR splice variants in parallel. We use this platform to quantitatively characterize the relative abundance of canonical and alternative receptor transcripts, their translational efficiency, and the plasma membrane expression of each receptor in the context of a recombinant pool of HEK293T cells expressing individual GPCRs. We then employ machine learning to identify specific structural features that are strongly associated with variations in GPCR expression. Our results show that many highly-expressed receptors exhibit systematic differences in hydrophobicity and secondary structure. This experimental platform and informatic approach are compatible with a variety of assays and can be used to efficiently explore the biochemical and pharmacological properties of the GPCRome.