An Effective and Safe Enkephalin Analog for Antinociception
Bibliographic record
Abstract
Opioids account for 69,000 overdose deaths per annum worldwide and cause serious side effects. Safer analgesics are urgently needed. The endogenous opioid peptide Leu-Enkephalin (Leu-ENK) is ineffective when introduced peripherally due to poor stability and limited membrane permeability. We developed a focused library of Leu-ENK analogs containing small hydrophobic modifications. N-pivaloyl analog KK-103 showed the highest binding affinity to the delta opioid receptor (68% relative to Leu-ENK) and an extended plasma half-life of 37 h. In the murine hot-plate model, subcutaneous KK-103 showed 10-fold improved anticonception (142%MPE·h) compared to Leu-ENK (14%MPE·h). In the formalin model, KK-103 reduced the licking and biting time to ~50% relative to the vehicle group. KK-103 was shown to act through the opioid receptors in the central nervous system. In contrast to morphine, KK-103 was longer-lasting and did not induce breathing depression, physical dependence, and tolerance, showing potential as a safe and effective analgesic.
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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) | 0.003 | 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".