A novel evolutionarily conserved domain of cell‐adhesion GPCRs mediates autoproteolysis
Bibliographic record
Abstract
The G protein-coupled receptor (GPCR) Proteolysis Site (GPS) of cell-adhesion GPCRs and polycystic kidney disease (PKD) proteins constitutes a highly conserved autoproteolysis sequence, but its catalytic mechanism remains unknown. Here, we show that unexpectedly the ∼40-residue GPS motif represents an integral part of a much larger ∼320-residue domain that we termed GPCR-Autoproteolysis INducing (GAIN) domain. Crystal structures of GAIN domains from two distantly related cell-adhesion GPCRs revealed a conserved novel fold in which the GPS motif forms five β-strands that are tightly integrated into the overall GAIN domain. The GAIN domain is evolutionarily conserved from tetrahymena to mammals, is the only extracellular domain shared by all human cell-adhesion GPCRs and PKD proteins, and is the locus of multiple human disease mutations. Functionally, the GAIN domain is both necessary and sufficient for autoproteolysis, suggesting an autoproteolytic mechanism whereby the overall GAIN domain fine-tunes the chemical environment in the GPS to catalyse peptide bond hydrolysis. Thus, the GAIN domain embodies a unique, evolutionarily ancient and widespread autoproteolytic fold whose function is likely relevant for GPCR signalling and for multiple human diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".