New Synthesis and Pharmacological Evaluation of Enantiomerically Pure (<i>R</i>)- and (<i>S</i>)-Methadone Metabolites as <i>N</i>-Methyl-<scp>d</scp>-aspartate Receptor Antagonists
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide N -Methyl- d -aspartate receptor (NMDAR) is gaining increasing interest as a pharmacological target for the development of fast-acting antidepressants. ( S )-Methadone (esmethadone), has recently shown promising efficacy for the treatment of major depressive disorder. However, methods for its enantiopure preparation still rely on complex and expensive resolution procedures. In addition, enantiopure methadone metabolites have never been evaluated for their NMDAR activity. Here, we report the development of a novel chiral pool approach, based on cyclic sulfamidate ring-opening reaction, for the asymmetric synthesis of ( R )- and ( S )-methadone, and the application of this methodology to the stereodivergent synthesis of 20 enantiopure methadone metabolites. The compounds were evaluated for their NMDAR antagonism and for their affinity toward a series of relevant CNS receptors. Strikingly, N -demethylated (6 R )-methadol metabolites retain the higher NMDAR uncompetitive antagonism of ( R )-methadone, while presenting lower opioid receptor affinity compared to ( S )-methadone. These compounds could represent novel candidates for drug development in CNS disorders.
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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) | 0.002 | 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".