Oxidation of Disulfides to Thiolsulfinates with Hydrogen Peroxide and a Cyclic Seleninate Ester Catalyst
Bibliographic record
Abstract
Cyclic seleninate esters function as mimetics of the antioxidant selenoenzyme glutathione peroxidase. They catalyze the reduction of harmful peroxides with thiols, which are converted to disulfides in the process. The possibility that the seleninate esters could also catalyze the further oxidation of disulfides to thiolsulfinates and other overoxidation products under these conditions was investigated. This has ramifications in potential medicinal applications of seleninate esters because of the possibility of catalyzing the unwanted oxidation of disulfide-containing spectator peptides and proteins. A variety of aryl and alkyl disulfides underwent facile oxidation with hydrogen peroxide in the presence of catalytic benzo-1,2-oxaselenolane Se-oxide affording the corresponding thiolsulfinates as the principal products. Unsymmetrical disulfides typically afforded mixtures of regioisomers. Lipoic acid and N,N'-dibenzoylcystine dimethyl ester were oxidized readily under similar conditions. Although isolated yields of the product thiolsulfinates were generally modest, these experiments demonstrate that the method nevertheless has preparative value because of its mild conditions. The results also confirm the possibility that cyclic seleninate esters could catalyze the further undesired oxidation of disulfides in vivo.
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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 | 0.000 | 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 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".