Differential β-Arrestin–Dependent Conformational Signaling and Cellular Responses Revealed by Angiotensin Analogs
Bibliographic record
Abstract
The angiotensin type 1 receptor (AT1R) and its octapeptide ligand, angiotensin II (AngII), engage multiple downstream signaling pathways, including those mediated by heterotrimeric guanosine triphosphate-binding proteins (G proteins) and those mediated by β-arrestin. Here, we examined AT1R-mediated Gα(q) and β-arrestin signaling with multiple AngII analogs bearing substitutions at position 8, which is critical for binding to the AT1R and its activation of G proteins. Using assays that discriminated between ligand-promoted recruitment of β-arrestin to the AT1R and its resulting conformational rearrangement, we extend the concept of biased signaling to include the analog's propensity to differentially promote conformational changes in β-arrestin, two responses that were differentially affected by distinct G protein-coupled receptor kinases. The efficacy of AngII analogs in activating extracellular signal-regulated kinases 1 and 2 correlated with the stability of the complexes between β-arrestin and AT1R in endosomes, rather than with the extent of β-arrestin recruitment to the receptor. In vascular smooth muscle cells, the ligand-induced conformational changes in β-arrestin correlated with whether the ligand promoted β-arrestin-dependent migration or proliferation. Our data indicate that biased signaling not only occurs between G protein- and β-arrestin-mediated pathways but also occurred at the level of the AT1R and β-arrestin, such that different AngII analogs selectively engaged distinct β-arrestin conformations, which led to specific signaling events and cell responses.
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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".