<i>N,N</i>-Diethyl-4-(phenylpiperidin-4-ylidenemethyl)benzamide: A Novel, Exceptionally Selective, Potent δ Opioid Receptor Agonist with Oral Bioavailability and Its Analogues
Bibliographic record
Abstract
The design, synthesis, and pharmacological evaluation of a novel class of delta opioid receptor agonists, N, N-diethyl-4-(phenylpiperidin-4-ylidenemethyl)benzamide (6a) and its analogues, are described. These compounds, formally derived from SNC-80 (2) by replacing the piperazine ring with a piperidine ring containing an exocyclic carbon carbon double bond, were found to bind with high affinity and exhibit excellent selectivity for the delta opioid receptor as full agonists. 6a, the simplest structure in the class, exhibited an IC(50) = 0.87 nM for the delta opioid receptors and extremely high selectivity over the mu receptors (mu/delta = 4370) and the kappa receptors (kappa/delta = 8590). Rat liver microsome studies on a selected number of compounds show these olefinic piperidine compounds (6) to be considerably more stable than SNC-80. This novel series of compounds appear to interact with delta opioid receptors in a similar way to SNC-80 since they demonstrate similar SAR. Two general approaches have been established for the synthesis of these compounds, based on dehydration of benzhydryl alcohols (7) and Suzuki coupling reactions of vinyl bromide (8), and are herewith reported.
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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 | 0.001 |
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".