Bioactivation of Nevirapine to a Reactive Quinone Methide: Implications for Liver Injury
Bibliographic record
Abstract
Nevirapine (NVP) treatment is associated with a significant incidence of liver injury. We developed an anti-NVP antiserum to determine the presence and pattern of covalent binding of NVP to mouse, rat, and human hepatic tissues. Covalent binding to hepatic microsomes from male C57BL/6 mice and male Brown Norway rats was detected on Western blots; the major protein had a mass of ~55 kDa. Incubation of NVP with rat CYP3A1 and 2C11 or human CYP3A4 also led to covalent binding. Treatment of female Brown Norway rats or C57BL/6 mice with NVP led to extensive covalent binding to a wide range of proteins. Co-treatment with 1-aminobenzotriazole dramatically changed the pattern of binding. The covalent binding of 12-hydroxy-NVP, the pathway that leads to a skin rash, was much less than that of NVP, both in vitro and in vivo. An analogue of NVP in which the methyl hydrogens were replaced by deuterium also produced less covalent binding than NVP. These data provide strong evidence that covalent binding of NVP in the liver is due to a quinone methide formed by oxidation of the methyl group. Attempts were made to develop an animal model of NVP-induced liver injury in mice. There was a small increase in ALT in some NVP-treated male C57BL/6 mice at 3 weeks that resolved despite continued treatment. Male Cbl-b(-/-) mice dosed with NVP had an increase in ALT of >200 U/L, which also resolved despite continued treatment. Liver histology in these animals showed focal areas of complete necrosis, while most of the liver appeared normal. This is a different pattern from the histology of NVP-induced liver injury in humans. This is the first study to report hepatic covalent binding of NVP and also liver injury in mice. It is likely that the quinone methide metabolite is responsible for NVP-induced liver injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".