Different Reactive Metabolites of Nevirapine Require Distinct Glutathione<i>S</i>-Transferase Isoforms for Bioinactivation
Bibliographic record
Abstract
Nevirapine (NVP) is a non-nucleoside reverse transcriptase-inhibitor, which is associated with severe idiosyncratic skin rash and hepatotoxicity. These adverse drug reactions are believed to be mediated by the formation of epoxides and/or quinone methide formed by oxidative metabolism by P450s and 12-sulfoxyl-NVP formed by sequential 12-hydroxylation and O-sulfonation. Although different GSH-conjugates and corresponding mercapturic acids have been demonstrated previously in vitro and in vivo, the role of the glutathione S-transferases in the inactivation of the different reactive metabolites has not been studied so far. In the present study the activity of 10 recombinant human glutathione S-transferases (GSTs) in the detoxification of the different reactive metabolites of NVP was studied. The results show that GSTP1-1 is a highly active catalyst of GSH-conjugation of the oxidative metabolites of NVP, even at high GSH-concentration. Experiments with trideuterated NVP suggest involvement of a reactive epoxide rather than quinone methide in the formation of the GSH-conjugate formed after oxidative bioactivation. GSH-conjugation of 12-sulfoxyl-NVP forming NVP-12-GSH was only catalyzed by GSTM1-1, GSTA1-1, and GSTA3-3. Although the exact expression levels of these enzymes in the skin is unknown, the relatively low activity of this catalysis makes it unlikely that GSTs can provide significant protection against this metabolite. However, since NVP-12-GSH is specifically formed via the 12-sulfoxyl-NVP, its corresponding urinary mercapturic acid can be considered as a biomarker for recent internal exposure to this protein-reactive sulfate. However, it has to be taken into account that 12-sulfoxyl-NVP is not completely trapped by GSH and that rates of bioinactivation will differ between patients due to variability in expression of GSTM1, GSTA1, and GSTA3.
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".