Optimization of a peptide ligand for the adhesion GPCR ADGRG2 provides a potent tool to explore receptor biology
Bibliographic record
Abstract
The adhesion GPCR ADGRG2, also known as GPR64, is a critical regulator of male fertility that maintains ion/pH homeostasis and CFTR coupling. The molecular basis of ADGRG2 function is poorly understood, in part because no endogenous ligands for ADGRG2 have been reported, thus limiting the tools available to interrogate ADGRG2 activity. It has been shown that ADGRG2 can be activated by a peptide, termed p15, derived from its own N-terminal region known as the Stachel sequence. However, the low affinity of p15 limits its utility for ADGRG2 characterization. In the current study, we used alanine scanning mutagenesis to examine the critical residues responsible for p15-induced ADGRG2 activity. We next designed systematic strategies to optimize the peptide agonist of ADGRG2, using natural and unnatural amino acid substitutions. We obtained an optimized ADGRG2 Stachel peptide T1V/F3Phe(4-Me) (VPM-p15) that activated ADGRG2 with significantly improved (>2 orders of magnitude) affinity. We then characterized the residues in ADGRG2 that were important for ADGRG2 activation in response to VPM-p15 engagement, finding that the toggle switch W 6.53 and residues of the ECL2 region of ADGRG2 are key determinants for VPM-p15 interactions and VPM-p15-induced Gs or arrestin signaling. Our study not only provides a useful tool to investigate the function of ADGRG2 but also offers new insights to guide further optimization of Stachel peptides to activate adhesion GPCR members.
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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) | 0.002 | 0.000 |
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".