Orphan receptor GPR37L1 remains unliganded

Tony Ngo, Brendan P. Wilkins, Sean S. So, Peter Keov, Kirti K. Chahal, Angela M. Finch, James L.J. Coleman, Irina Kufareva, Nicola J. Smith

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Orphan G-protein-coupled receptors (GPCRs) are largely intractable therapeutic targets, owing to the lack of chemical tools for exploring their pharmacology. The discovery of such tools, however, is hampered by a number of unknowns, such as effector coupling and appropriate positive controls. In our 2017 Nature Chemical Biology paper1, we developed a computational chemical tool discovery approach called GPCR Contact-Informed Neighboring Pocket (GPCR-CoINPocket). This method predicted pharmacological similarity of GPCRs in a ligand- and structure-independent manner, to enable the discovery of off-target activities of known compounds at orphan GPCRs and hence the identification of so-called surrogate ligands. Our orphan GPCR target for prospective surrogate ligand discovery efforts was GPR37L1, a brain-specific receptor linked to cerebellar development2 and seizures3. We had previously demonstrated that GPR37L1 constitutively coupled to Gαs and generated ligand-independent increases in intracellular cyclic AMP (cAMP)4. Thus, the inverse agonist activities of computationally predicted surrogates were tested in a cAMP-response element (CRE)–luciferase reporter gene assay in human embryonic kidney (HEK293) cells expressing either vector control or what we thought was untagged GPR37L1 in pcDNA3.1. However, we recently discovered that the GPR37L1 construct used in both studies was incorrect: instead of pcDNA3.1, the receptor was inserted backwards into a yeast p426GPD vector (hereafter referred to as p426-r37L1). We reported the issue to the editors of Science Signaling and Nature Chemical Biology, which eventually led to the retraction of both papers1,4. Here we correct the cloning error and describe our subsequent unsuccessful efforts to retest the computationally predicted GPR37L1 ligands.
Original languageEnglish
Pages (from-to)383-386
Number of pages4
JournalNature Chemical Biology
Volume17
Issue number4
DOIs
Publication statusPublished - 1 Mar 2021
Externally publishedYes

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