[2‘,6‘-Dimethyltyrosine]Dynorphin A(1−11)-NH<sub>2</sub>Analogues Lacking an N-Terminal Amino Group: Potent and Selective κ Opioid Antagonists
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Bibliographic record
Abstract
Recent studies showed that dermorphin and enkephalin analogues containing two methyl groups at the 2',6'-positions of the Tyr(1) aromatic ring and lacking an N-terminal amino group were moderately potent delta and mu opioid antagonists. These results indicate that a positively charged N-terminal amino group may be essential for signal transduction but not for receptor binding and suggested that its deletion in agonist opioid peptides containing an N-terminal 2',6'-dimethyltyrosine (Dmt) residue may represent a general way to convert them into antagonists. In an attempt to develop dynorphin A (Dyn A)-derived kappa opioid antagonists, we prepared analogues of [Dmt(1)]Dyn A(1-11)-NH2 (1), in which the N-terminal amino group was either omitted or replaced with a methyl group. This was achieved by replacement of Tyr(1) with 3-(2,6-dimethyl-4-hydroxyphenyl)propanoic acid (Dhp) or (2S)-2-methyl-3-(2,6-dimethyl-4-hydroxyphenyl)propanoic acid [(2S)-Mdp]. Compounds were tested in the guinea pig ileum and mouse vas deferens bioassays and in rat and guinea pig brain membrane receptor binding assays. All analogues turned out to be potent kappa antagonists against Dyn A(1-13) and the non-peptide agonist U50,488 and showed only weak mu and delta antagonist activity. The most potent and most selective kappa antagonist of the series was [(2S)-Mdp(1)]Dyn A(1-11)-NH2 (5, dynantin), which showed subnanomolar kappa antagonist potency against Dyn A(1-13) and very high kappa selectivity both in terms of its K(e) values determined against kappa, mu, and delta agonists and in terms of its ratios of kappa, mu, and delta receptor binding affinity constants. Dynantin is the first potent and selective Dyn A-derived kappa antagonist known and may complement the non-peptide kappa antagonists norbinaltorphimine and GNTI as a pharmacological tool in opioid research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 it