Preparation and Evaluation at the Delta Opioid Receptor of a Series of Linear Leu-Enkephalin Analogues Obtained by Systematic Replacement of the Amides
Bibliographic record
Abstract
Leu-enkephalin analogues, in which the amide bonds were sequentially and systematically replaced either by ester or N-methyl amide bonds, were prepared using classical organic chemistry as well as solid phase peptide synthesis (SPPS). The peptidomimetics were characterized using competition binding, ERK1/2 phosphorylation, receptor internalization, and contractility assays to evaluate their pharmacological profile over the delta opioid receptor (DOPr). The lipophilicity (LogD7.4) and plasma stability of the active analogues were also measured. Our results revealed that the last amide bond can be successfully replaced by either an ester or an N-methyl amide bond without significantly decreasing the biological activity of the corresponding analogues when compared to Leu-enkephalin. The peptidomimetics with an N-methyl amide function between residues Phe and Leu were found to be more lipophilic and more stable than Leu-enkephalin. Findings from the present study further revealed that the hydrogen-bond donor properties of the fourth amide of Leu-enkephalin are not important for its biological activity on DOPr. Our results show that the systematic replacement of amide bonds by isosteric functions represents an efficient way to design and synthesize novel peptide analogues with enhanced stability. Our findings further suggest that such a strategy can also be useful to study the biological roles of amide bonds.
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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 | 0.000 |
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 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".