Prostaglandin F2α and angiotensin II type 1 receptors exhibit differential cognate G protein coupling regulation
Bibliographic record
Abstract
Promiscuous G protein-coupled receptors (GPCRs) engage multiple Gα subtypes with different efficacies to propagate signals in cells. A mechanistic understanding of Gα selectivity by GPCRs is critical for therapeutic design, since signaling can be restrained by ligand-receptor complexes to preferentially engage specific G proteins. However, details of GPCR selectivity are unresolved. Here, we investigated cognate G protein selectivity using the prototypical promiscuous Gαq/11 and Gα12/13 coupling receptors, angiotensin II type I receptor (AT1R) and prostaglandin F2α receptor (FP), bioluminescence resonance energy transfer-based G protein and pathway-selective sensors, and G protein knockout cells. We determined that competition between G proteins for receptor binding occurred in a receptor- and G protein-specific manner for AT1R and FP but not for other receptors tested. In addition, we show that while Gα12/13 competes with Gαq/11 for AT1R coupling, the opposite occurs for FP, and Gαq-mediated signaling regulated G protein coupling only at AT1R. In cells, the functional modulation of biased ligands at FP and AT1R was contingent upon cognate Gα availability. The efficacy of AT1R-biased ligands, which poorly signal through Gαq/11, increased in the absence of Gα12/13. Finally, we show that a positive allosteric modulator of Gαq/11 signaling that also allosterically decreases FP-Gα12/13 coupling, lost its negative modulation in the absence of Gαq/11 coupling to FP. Together, our findings suggest that despite preferential binding of similar subsets of G proteins, GPCRs follow distinct selectivity rules, which may contribute to the regulation of ligand-mediated G protein bias of AT1R and FP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".