Substrate Specificity of Human Cytochrome P450 (CYP) 2C Subfamily and Effect of Azole Antifungal Agents on CYP2C8
Bibliographic record
Abstract
PURPOSE: The metabolic activities of aminopyrine N-demethylation and tolbutamide methylhydroxylation by the human hepatic cytochrome P450 (P450 or CYP) 2C subfamily were compared and the effects of azole antifungal agent on the drug-metabolizing activity of CYP2C8 were investigated. METHODS: Aminopyrine N-demethylation and tolbutamide methylhydroxylation by CYP2C8, CYP2C9, and CYP2C19 were determined by the previous reported methods. The effects of five azole antifungal agents, fluconazole, itraconazole, ketoconazole, miconazole, and voriconazole, on the aminopyrine N-demethylation activity by CYP2C8 were investigated. RESULTS: With regard to aminopyrine N-demethylation, CYP2C19 had the lowest Michaelis constant (Km) and CYP2C8 had the highest maximal velocity (Vmax) among the CYP2C subfamily members. The Vmax/Km values for CYP2C8 were the highest, followed by CYP2C19. For tolbutamide methylhydroxylation, the Km and Vmax for CYP2C19 were three and six times higher than the corresponding values for CYP2C9, and the Vmax/Km value for CYP2C19 was twice that for CYP2C9, whereas hydroxylated tolbutamide formed by CYP2C8 was not detected. Fluconazole, itraconazole, and voriconazole at a concentration of 2 or 10 µM neither inhibited nor stimulated CYP2C8-mediated aminopyrine N-demethylation activity at substrate concentrations around the Km (5 mM). However, ketoconazole and miconazole noncompetitively inhibited CYP2C8-mediated aminopyrine N-demethylation with the inhibitory constant values of 1.98 and 0.86 µM, respectively. CONCLUSION: These results suggest that ketoconazole and miconazole might inhibit CYP2C8 clinically. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.001 |
| 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".