Protein S-Glutathiolation Triggered by Decomposed<i>S</i>-Nitrosoglutathione
Bibliographic record
Abstract
Recombinant human brain calbindin D(28K) (rHCaBP), human Cu,Zn-superoxide dismutase (HCuZnSOD), rabbit muscle glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and bovine serum albumin (BSA) were found to be S-glutathiolated in decomposed S-nitrosoglutathione (GSNO) solutions. Tryptic or Glu-C digestion and MALDI-TOF MS analyses of the digests are consistent with S-thiolation of Cys111 and Cys187 of HCuZnSOD and rHCaBP, respectively, upon exposure to decomposed GSNO. GAPDH activity analysis reveals that S-glutathiolation most likely occurs on the active site Cys149, and the single free Cys34 is assumed to be the site of S-glutathiolation in BSA. The yields of S-glutathiolation of rHCaBP, GAPDH, and BSA were much higher than those of HCuZnSOD. The latter is limited by the accessibility of Cys111 to the glutathiolating reagent in the HCuZnSOD dimer. Unlike decomposed GSNO, fresh GSNO, reduced glutathione (GSH), and oxidized glutathione (GSSG) are not efficient S-glutathiolating agents for the proteins examined here. On the basis of analysis by mass spectrometry and UV-visible absorption, GSNO decomposition in the dark at room temperature yields glutathione disulfide S-oxide [GS(O)SG], glutathione disulfide S-dioxide (GSO(2)SG), and GSSG as products. GS(O)SG is the efficient protein S-glutathiolating agent in GSNO solutions, not GSNO, which does not carry out efficient S-glutathiolation of rHCaBP, HCuZnSOD, or GAPDH in vitro. A hydrolysis pathway yielding GSOH and nitroxyl (HNO/NO(-)) as intermediates is proposed for GSNO decomposition in the dark. This is based on inhibition of GSNO breakdown by dimedone, a reagent specific for sulfenic acids, and on nitroxyl scavenging by metmyoglobin. The results presented here are contrary to numerous reports of protein S-thiolation by low-molecular weight S-nitrosothiols.
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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 | 0.000 |
| 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) | 0.000 | 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 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".