Determining site occupancy of acetaminophen covalent binding to target proteins in vitro
Bibliographic record
Abstract
Abstract Acetaminophen (APAP)‐related toxicity is caused by the formation of N ‐acetyl p ‐benzoquinone imine (NAPQI), a reactive metabolite able to covalently bind to protein thiols. A targeted liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) method, using multiple reaction monitoring (MRM), was developed to measure APAP binding on selected target proteins, including glutathione S ‐transferases (GSTs). In vitro incubations with CYP3A4 were performed to form APAP in the presence of different proteins, including four purified GST isozymes. A custom alkylation agent was used to prepare heavy labeled modified protein containing a structural isomer of APAP on all cysteine residues for isotope dilution. APAP incubations were spiked with heavy labeled protein, digested with either trypsin or pepsin, followed by peptide fractionation by HPLC prior to LC‐MRM analysis. Relative site occupancy on the protein‐level was used for comparing levels of modification of different sites in target proteins, after validation of protein and peptide‐level relative quantitation using human serum albumin as a model system. In total, seven modification sites were quantified, namely Cys115 and 174 in GSTM2, Cys15, 48 and 170 in GSTP1, and Cys50 in human MGST1 and rat MGST1. In addition, APAP site occupancies of three proteins from liver microsomes were also quantified by using heavily labeled microsomes spiked into APAP microsomal incubations. A novel approach employing an isotope‐labeled alkylation reagent was used to determine site occupancies on multiple protein thiols.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".