G protein selectivity profile of GPR56/ADGRG1 and its effect on downstream effectors
Bibliographic record
Abstract
GPR56, an adhesion G-protein coupled receptor (aGPCRs) with constitutive and ligand-promoted activity, is involved in many physiological and pathological processes. Whether the receptor's constitutive or ligand-promoted activation occur through the same molecular mechanism, and whether different activation modes lead to functional selectivity between G proteins is unknown. Here we show that GPR56 constitutively activates both G12 and G13. Unlike constitutive activation and activation with 3-α-acetoxydihydrodeoxygedunin (3αDOG), stimulation with an antibody, 10C7, directed against GPR56's extracellular domain (ECD) led to an activation that favors G13 over G12. An autoproteolytically deficient mutant, GPR56-T383A, was also activated by 10C7 indicating that the tethered agonist (TA) exposed through autocatalytic cleavage, is not required for this activation modality. In contrast, this proteolysis-resistant mutant could not be activated by 3αDOG indicating different modes of activation by the two ligands. We show that an N-terminal truncated GPR56 construct (GPR56-Δ1-385) is devoid of constitutive activity but was activated by 3αDOG. Similarly to 3αDOG, 10C7 promoted the recruitment of β-arrestin-2 but GPR56 internalization was β-arrestin independent. Despite the slow activation mode of 10C7 that favors G13 over G12, it efficiently activated the downstream Rho pathway in BT-20 breast cancer cells. These data show that different GPR56 ligands have different modes of activation yielding differential G protein selectivity but converging on the activation of the Rho pathway both in heterologous expressions system and in cancer cells endogenously expressing the receptor. 10C7 is therefore an interesting tool to study both the processes underlying GPR56 activity and its role in cancer cells.
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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 | 0.000 |
| 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".