Peptide and Non-peptide Antagonists Targeting Endothelin Receptors in Physiology and Pathology
Bibliographic record
Abstract
As for other peptides such as bradykinin, neurokinins and angiotensins, peptide antagonists for endothelin-1 (ET-1) have been early on developed towards the pharmacological characterization of both ETA and ETB receptors. Interestingly, unlike the previously mentioned three peptides, receptors for ET-1 were cloned and purified prior to the report of ETA and ETB receptor antagonists such as BQ-123 and BQ-788. The availability of such pharmacological tools and the use of molecular approaches have certainly fast-tracked the development of non-peptide ET receptor antagonists for clinical applications. Albeit rapid degradation by gastric enzymes and short halflife in plasma of peptide receptor antagonists limit their use in clinical settings, those molecules have been of importance in the identification of mediators and modulators of ET-1 induced properties in vitro and in vivo, as described further in this review. Peptide antagonists acting selectively or, with equivalent affinities against ETA and ETB receptors were reported prior to the advent of clinically relevant non-peptide blockers such as Bosentan. Confounding mechanisms involving, for example, the endogenous modulators nitric oxide and prostacyclin as well as allosteric interactions between ET receptor types, have also been clarified with the use of peptide antagonists for endothelins. Finally, peptide antagonists were also used to identify the precise pharmacology of ET-1 precursors such as big-endothelin-1 and ET-1 (1-31). The present review will thus attempt to summarize the knowledge to date and future perspectives related to use of peptide antagonists targeting endothelin receptors in physiological and pathological settings. Keywords: Endothelin-1, antagonists, ETA and ETB receptors, Streptomyces misakiensis, amino acid isoforms, disulfide bonds, pulmonary hypertension, sulfamethoxazole, subarachnoid hemorrhage, Salicylic acid, Neurogenesis, Hippocampus, Neuroblast, Rostral migratory stream, brain tumor stem cell, NG2, Ependyma, Stem cell, dentate gyrus, subgranular zone, cytokine, PSA-NCAM, Ki67, Interleukin
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".