Changes in amino-terminal portion of human B<sub>2</sub>receptor selectively increase efficacy of synthetic ligand HOE 140 but not of cognate ligand bradykinin
Bibliographic record
Abstract
Recently, we have shown that a widely used antagonist of the human bradykinin B(2) receptor (B(2)R) HOE 140 acts as a full agonist of the chicken ornithokinin receptor (B(o)R). To understand the molecular mechanisms underlying differential efficacy of HOE 140 for the various kinin receptors, we have constructed chimeric kinin receptors (CKR) in which the amino-terminal portion including the first two transmembrane regions and the first extracellular loop (CKR-2) or only the second transmembrane region and the first extracellular loop (CKR-1) of B(2)R were substituted with the corresponding segments of B(o)R. Ligand efficacy of synthetic ligand HOE 140 decreased in the order B(o)R > CKR-2 > CKR-1 > B(2)R, whereas the efficacy of the endogenous kinin ligand was unchanged. Enhanced HOE 140 efficacy was not due to a structural change in the ligand binding site or to an enhanced receptor expression level. Rather, heterologous binding competition studies indicated that structural change(s) introduced into the engineered receptors caused a selective reduction in apparent affinity of HOE 140 for the uncoupled inactive receptor state R but not for the active G protein-coupled state R*, thereby increasing the ratio of R* over R for a given ligand concentration. Our results may help explain the unusually broad efficacy spectrum of HOE 140, which varies from inverse to full agonism, depending on kinin receptor subtype, tissue origin, or species.
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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 | 0.001 |
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".