Catechin Metabolism: Glutathione Conjugate Formation Catalyzed by Tyrosinase, Peroxidase, and Cytochrome P450
Bibliographic record
Abstract
The metabolic pathways of dietary flavonoids are still largely unknown. In the present work, mass spectrometry and UV-vis spectroscopy studies were used to show that the naturally occurring flavonoid catechin underwent enzymatic oxidation by tyrosinase in the presence of glutathione (GSH) to form mono-, bi-, and tri-glutathione conjugates of catechin and mono- and bi-glutathione conjugates of a catechin dimer. A hydroxylated catechin adduct was also detected. Using UV spectroscopy, it was shown that the catechol B-ring of catechin was oxidized by tyrosinase to form an o-quinone which could be reduced back to catechin with potassium borohydride or reacted with GSH to form glutathione conjugates. The catechin-glutathione conjugates formed had much lower distribution coefficient values than catechin itself. When peroxidase and hydrogen peroxide were used instead of tyrosinase, only mono-glutathione conjugates were formed but not bi-glutathione conjugates or hydroxylated adducts. (1)H NMR evidence showed that three different mono-glutathione conjugates on ring B of catechin were formed by peroxidase and hydrogen peroxide. Rat liver microsomes and NADPH or cumene hydroperoxide also catalyzed catechin-glutathione conjugate formation which was prevented by benzylimidazole, a P450 2E1 inhibitor. Catechin cytotoxicity toward isolated hepatocytes was also markedly enhanced by hydrogen peroxide or cumene hydroperoxide and was prevented by benzylimidazole, suggesting that catechin could be metabolically activated by P450 peroxidase activity to form cytotoxic quinoid species.
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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 | 0.000 |
| 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".