Recent Advances in 5-HT1B / 1D Receptor Antagonists and Agonists and their Potential Therapeutic Applications
Bibliographic record
Abstract
The human 5-HT(1B) and 5-HT(1D) receptors are especially similar in sequence despite being encoded by two distinct genes. Although, human 5-HT(1B) and 5-HT(1D) receptors have been pharmacologically differentiated using nonselective 5-HT(1B/D) receptor antagonists such as ketanserin (1), ritanserin (2) and methiothepin (3), the precise function of these receptors remains undefined, and progress toward this has been hampered by the lack of selective ligands. The interest of the major pharmaceutical companies in 5-HT(1B/1D) antagonists increased by the discovery of potent and selective tools, combined with the fact that the blockade of terminal 5-HT(1B) receptors by selective antagonists has been proposed as a new approach for more efficient and/or fast-acting antidepressant drugs, since the acute blockade of these 5-HT autoreceptors will, in theory, immediately mimic their desensitization. Furthermore, it has been also suggested that supersensitive 5-HT(1B/1D) receptors may be involved in the pathophysiology of obsessive compulsive disorders (OCD). In the 5-HT(1B/1D) agonist field, since the discovery of sumatriptan (26) (a 5-HT(1B/1D) receptor agonist) as an effective treatment for migraine headache, intensive research in this area has led to several second-generation compounds, a few of which have either entered the market place or are in late clinical trials. Beside the antimigraine activity of the 5-HT(1B/1D) agonists in clinical evaluation or already on the market, other potential therapeutic evaluations (such as gastric motor effect, bipolar disorder, autism, anti-aggressive effects) with these drugs are being investigated. This article highlights and reviews the research advances published in the 5-HT(1B/1D) antagonist and agonist literature. The article is supplemented with selected references on the design, synthesis and development of novel 5-HT(1B/1D) agents, and on studies to understand their mechanism and pathophysiology. Emphasis is given to recent advances in the potential therapeutic applications of 5-HT(1B/1D) serotonergic agents. By no means has any attempt been made to exhaustively review the literature but rather, primary references along with citations to recent literature reviews have been included in each section.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".