Cyclic Opioid Peptide Agonists and Antagonists Obtained Via Ring‐Closing Metathesis
Bibliographic record
Abstract
The opioid peptide H-Tyr-c[D-Cys-Phe-Phe-Cys]NH(2) cyclized via a methylene dithiother is a potent and selective mu opioid agonist (Przydial M.J. et al., J Peptide Res, 66, 2005, 255). Dicarba analogues of this peptide with Tyr, 2',6'-dimethyltyrosine (Dmt), 3-[2,6-dimethyl-4-hydroxyphenyl)propanoic acid (Dhp) or (2S)-2-methyl-3-(2,6-dimethyl-4-hydroxyphenyl)propanoic acid [(2S)-Mdp] in the 1-position were prepared. The peptides were synthesized on solid-phase by substituting d-allylglycine and (2S)-2-amino-5-hexenoic acid in position 2 and 5, respectively, followed by ring-closing metathesis. Mixtures of cis and trans isomers of the resulting olefinic peptides were obtained, and catalytic hydrogenation yielded the saturated -CH(2)-CH(2)- bridged peptides. All six Tyr(1)- and Dmt(1)-dicarba analogues retained high mu and delta opioid agonist potency and showed only slight or no preference for mu over delta receptors. As expected, the six Dhp(1)- and (2S)-Mdp(1)-dicarba analogues turned out to be mu opioid antagonists but, surprisingly, displayed a range of different efficacies (agonism, partial agonism or antagonism) at the delta receptor. The obtained results indicate that the mu versus delta receptor selectivity and the efficacy at the delta receptor of these cyclic peptides depend on distinct conformational characteristics of the 15-membered peptide ring structure, which may affect the spatial positioning of the exocyclic residue and of the Phe(3) and Phe(4) side chains.
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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) | 0.001 | 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".