Understanding P450‐mediated Bio‐transformations into Epoxide and Phenolic Metabolites
Bibliographic record
Abstract
Adverse drug reactions are commonly the result of cytochrome P450 enzymes (CYPs) converting the drugs into reactive metabolites. Thus, information about the CYP bioactivation of drugs would not only provide insight into metabolic stability, but also into the potential toxicity. For example, oxidation of phenyl rings may lead to either toxic epoxides or safer phenols. Herein, we demonstrate that the potential to form reactive metabolites is encoded primarily in the properties of the molecule to be oxidized. While the enzyme positions the molecule inside the binding pocket (selects the site of metabolism), the subsequent reaction is only dependent on the substrate itself. To test this hypothesis, we used this observation as a predictor of drug inherent toxicity. This approach was used to successfully identify the formation of reactive metabolites in over 100 drug molecules. These results provide a new perspective on the impact of functional groups on aromatic oxidation of drugs and their effects on toxicity.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".