Differential inhibition and inactivation of human CYP1 enzymes by trans-resveratrol: evidence for mechanism-based inactivation of CYP1A2.
Bibliographic record
Abstract
trans-Resveratrol (3,5,4'-trihydroxy-trans-stilbene) has been reported to confer chemoprotection against 7,12-dimethylbenz[a]anthracene (DMBA)-induced carcinogenicity in a murine model. A potential mechanism for this effect by trans-resveratrol is inhibition of DMBA-bioactivating cytochrome P450 (CYP) enzymes such as CYP1B1, CYP1A1, and CYP1A2. In the present study, we examined in detail the in vitro inhibitory effects of trans-resveratrol on these three human CYP enzymes. trans-Resveratrol decreased 7-ethoxyresorufin O-dealkylation activity catalyzed by human recombinant CYP1B1, CYP1A1, and CYP1A2 in a concentration-dependent manner and by a mixed type of inhibition. This direct inhibition was enzyme-selective, as judged by the differences in the apparent K(i) values (0.8 +/- 0.1 microM, 1.2 +/- 0.1 microM, and 15.5 +/- 1.1 microM for CYP1B1, CYP1A1, and CYP1A2, respectively). Preincubating recombinant CYP1A2 or human liver microsomes with trans-resveratrol and NADPH prior to the initiation of substrate oxidation resulted in a time- and concentration-dependent decrease in catalytic activity. The inactivation of liver microsomal CYP1A2 by trans-resveratrol required NADPH, was not reversible by dialysis, and was not affected by the trapping agents glutathione, N-acetylcysteine, catalase, or superoxide dismutase, but was attenuated by a CYP1A2 substrate, imipramine. Analysis of a panel of individual human liver microsomes showed intersample differences in the response to the in vitro inactivation by trans-resveratrol. In contrast to CYP1A2, CYP1B1 was not subject to inactivation by this compound and the reduction in CYP1A1 activity was time- but not concentration-dependent. In summary, trans-resveratrol differentially inhibited human CYP1 enzymes and this occurred by two distinct mechanisms: direct inhibition (mainly CYP1B1 and CYP1A1) and mechanism-based inactivation (CYP1A2).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".