Identification of human cytochrome P450 enzymes involved in the hepatic and intestinal biotransformation of 20(<i>S</i>)‐protopanaxadiol
Bibliographic record
Abstract
20(S)-Protopanaxadiol (aPPD), a ginseng sapogenin, has been shown to be a promising anti-cancer compound and anti-depressant agent. Although the bacterial biotransformation of ginsenosides has been studied thoroughly, few have reported on the cytochrome P450 (P450) mediated metabolism of aPPD. Taken orally, aPPD must first undergo absorption and metabolism in the intestine before further metabolism in the liver. The present study investigated the comparative biotransformation profile of aPPD in human intestinal microsomes (HIM) and human liver microsomes (HLM) and characterized the human P450 enzymes involved in aPPD metabolism. Three major monooxygenated metabolites and five minor dioxygenated metabolites were identified as the predominant products in aPPD incubations with HIM and HLM using liquid chromatography-mass spectrometry. Reaction phenotyping studies were performed with a panel of specific P450 chemical inhibitors, antibody inhibition and human recombinant P450 enzymes. Ketoconazole, a CYP3A inhibitor, blocked the formation of oxygenated metabolites of aPPD in both HIM and HLM in a concentration dependent manner. Among the human recombinant P450 enzymes assayed, CYP3A4 exhibited the highest activity towards aPPD oxidative metabolite formation, followed by CYP3A5. In summary, the results have shown that aPPD is extensively metabolized by HIM and the metabolite profile following in vitro incubations is similar in HIM and HLM. CYP3A4 and CYP3A5 isoforms are the predominant enzymes responsible for oxygenation of aPPD in HIM and HLM. The characterization of aPPD as a CYP3A substrate may facilitate better prediction of drug-herb interactions when aPPD is taken concomitantly with other therapeutic agents.
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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 | 0.000 |
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".