Cytochrome P450 2D6 and 3A4 enzyme inhibition by amine stimulants in dietary supplements
Bibliographic record
Abstract
A number of dietary supplements used for weight loss and athletic performance enhancement have been recently shown to contain a variety of stimulants, for which there is a lack of pharmacological and toxicological information. One concern for these emerging compounds is their potential to inhibit metabolic enzymes in the liver such as cytochromes P450 (CYP), which can lead to unexpected interactions among dietary supplements, drugs, and other xenobiotics. In this study, inhibition of human recombinant CYP2D6 and CYP3A4 by 27 amine stimulants associated with dietary supplements and their analogs was evaluated by luminescence assays. The strongest CYP2D6 inhibitors were coclaurine (IC50 = 0.14 ± 0.01 μM) and N-benzylphenethylamine (IC50 = 0.7 ± 0.2 μM), followed by several other relatively strong inhibitors (IC50 , 2-12 μM) including β-methylphenethylamine, N,β-dimethylphenethylamine (phenpromethamine), 1,3-dimethylamylamine (DMAA), N,α-diethylphenethylamine, higenamine (norcoclaurine) and N,N-diethylphenethylamine. Only nine compounds inhibited CYP3A4 by 20-55% at 100 μM. Results of this study illustrate that several amine stimulants associated with dietary supplements inhibit CYP2D6 and CYP3A4 in vitro, and these compounds may participate in adverse drug-dietary supplement interactions in vivo. Copyright © 2015 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".