Metabolism of N,N-dialkylated amphetamines, including deprenyl, by CYP2D6 expressed in a human cell line
Bibliographic record
Abstract
1. Five N,N-dialkylated amphetamines, N-methyl-N-propargylamphetamine (deprenyl; DEP), N-benzyl-N-methylamphetamine (benzphetamine; BPA), N-allyl-N-methylamphetamine (AMA), N,N-diallylamphetamine (DAA) and N-methyl-N-propylamphetamine (MPA), were metabolized in vitro with a microsomal preparation from cells expressing human CYP2D6 to determine what influence the N,N-dialkyl substituents had on the extent of N-dealkylation and/or aromatic ring oxidation. 2. The results obtained from experiments with the first two substrates, DEP and BPA, were surprisingly different. Whereas DEP was N-demethylated and N-depropargylated by the CYP2D6 enzyme system, no metabolites were formed from BPA. Subsequently, it was determined that AMA, DAA and MPA also underwent CYP2D6-catalysed N-dealkylation. Both N-methyl- and N-allylamphetamine were identified as products of AMA metabolism; similarly, metabolism of MPA produced both N-methyl- and N-propargylamphetamine, and N-allylamphetamine was the sole metabolite of DAA. 3. No N,N-didealkylated product (i.e. amphetamine) was isolated from incubates of any of the five substrates, and none of the N,N-dialkylated substrates was metabolized to a ring-hydroxylated product. 4. Rates of these CYP2D6-catalysed reactions were dependent on the nature and degree of unsaturation of the N-substituents.
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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 | 0.001 |
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".