Inverse Agonism of SQ 29,548 and Ramatroban on Thromboxane A2 Receptor
Bibliographic record
Abstract
G protein-coupled receptors (GPCRs) show some level of basal activity even in the absence of an agonist, a phenomenon referred to as constitutive activity. Such constitutive activity in GPCRs is known to have important pathophysiological roles in human disease. The thromboxane A2 receptor (TP) is a GPCR that promotes thrombosis in response to binding of the prostanoid, thromboxane A2. TP dysfunction is widely implicated in pathophysiological conditions such as bleeding disorders, hypertension and cardiovascular disease. Recently, we reported the characterization of a few constitutively active mutants (CAMs) in TP, including a genetic variant A160T. Using these CAMs as reporters, we now test the inverse agonist properties of known antagonists of TP, SQ 29,548, Ramatroban, L-670596 and Diclofenac, in HEK293T cells. Interestingly, SQ 29,548 reduced the basal activity of both, WT-TP and the CAMs while Ramatroban was able to reduce the basal activity of only the CAMs. Diclofenac and L-670596 showed no statistically significant reduction in basal activity of WT-TP or CAMs. To investigate the role of these compounds on human platelet function, we tested their effects on human megakaryocyte based system for platelet activation. Both SQ 29,548 and Ramatroban reduced the platelet hyperactivity of the A160T genetic variant. Taken together, our results suggest that SQ 29,548 and Ramatroban are inverse agonists for TP, whereas, L-670596 and Diclofenac are neutral antagonists. Our findings have important therapeutic applications in the treatment of TP mediated pathophysiological conditions.
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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) | 0.001 | 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".