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Cited by 8Receptor Mechanisms and SignalingProtein Structure and DynamicsProtein Kinase Regulation and GTPase Signaling

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Generic residue numbering of the GAIN domain of adhesion GPCRs

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Seufert, Florian, Pérez-Hernández, Guillermo, Pándy-Szekeres, Gáspár, Guixà-González, Ramon, Langenhan, Tobias, Gloriam, David E., Hildebrand, Peter W.·2025·Nature Communications
DOI 10.1038/s41467-024-55466-6PMC PMC11697300

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Abstract

The GPCR autoproteolysis inducing (GAIN) domain is an ancient protein fold ubiquitous in adhesion G protein-coupled receptors (aGPCR). It contains a tethered agonist necessary and sufficient for receptor activation. The GAIN domain is a hotspot for pathological mutations. However, the low primary sequence conservation of GAIN domains has thus far hindered the knowledge transfer across different GAIN domains in human receptors as well as species orthologs. Here, we present a scheme for generic residue numbering of GAIN domains, based on structural alignments of over 14,000 modeled GAIN domain structures. This scheme is implemented in the GPCR database (GPCRdb) and elucidates the domain topology across different aGPCRs and their homologs in a large panel of species. We identify conservation hotspots and statistically cancer-enriched positions in human aGPCRs and show the transferability of positional and structural information between GAIN domain homologs. The GAIN-GRN scheme provides a robust strategy to allocate structural homologies at the primary and secondary levels also to GAIN domains of polycystic kidney disease 1/PKD1-like proteins, which now renders positions in both GAIN domain types comparable to one another. In summary, our work enables researchers to generate hypothesis and rationalize experiments related to GAIN domain function and pathology.

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Metadata

Authors
Seufert, F., Pérez-Hernández, G., Pándy-Szekeres, G., Guixà-González, R., Langenhan, T., Gloriam, D. E., & Hildebrand, P. W.
Affiliations
  • Leipzig University (DE)
  • University of Copenhagen (DK)
  • Center for Scalable Data Analytics and Artificial Intelligence (DE)
Corresponding author
  • Gloriam, David E.
  • Hildebrand, Peter W.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2025-01-02
Volume
16
Issue
1
Pages
246-246
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-024-55466-6
PMC
PMC11697300
OpenAlex
W4406016732
Cited by
8
References
2
Citations by year
2026: 3 · 2025: 5
FWCI
2.40
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Deutsche Forschungsgemeinschaft (421152132)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
Keywords
GAIN domain, adhesion G protein-coupled receptors, tethered agonist, receptor activation, structural alignment, GPCRdb, conservation hotspots, PDZ domain, structural homology
MeSH terms
Protein Domains, Amino Acid Sequence, Animals, Humans, Models, Molecular, Databases, Protein, Receptors, G-Protein-Coupled

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