Rapid high‐yield <i>N</i>‐acylation of aminothiols: <i>N</i>‐acetylglutathione and <i>N</i>‐acetylhomocysteine and their thiol p<i>K</i><sub>a</sub> values
Bibliographic record
Abstract
Methodology for the rapid N-acylation of aminothiols in aqueous solution using procedures commonly employed in biochemical studies is described here. Glutathione disulfide (GSSG) and homocystine were diN-acetylated in ~100% yield in 0.1 M aqueous NaHCO3 (pH 8.5) at room temperature by 2.5 equiv of the activated ester, N-hydroxysulfosuccinimidyl acetate, an efficient water-soluble acetylating reagent. Following acetone precipitation, diN-acetylGSSG was further purified and desalted on a strong anion-exchange (SAX) cartridge. DiN-acetylhomocystine was simultaneously purified and desalted on a C18 cartridge. The N-acetylated aminothiols were generated using gel-immobilized tris(2-carboxyethyl)phosphine as a reductant, which obviated the need for further purification. Alternatively, disulfide exchange with dissolved dithiothreitol yielded N-acetylglutathione, which was purified on the SAX cartridge. pH titrations of N-acetylglutathione (8.99) and N-acetylhomocysteine (9.66) as well as those of commercially available N-acetylcysteine (9.53) and N-acetylpenicillamine (10.21) yielded pK(a) (SH) values of importance for biological studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".