Fluxional Cyclic Seleninate Ester: NMR and Computational Studies, Glutathione Peroxidase-like Behavior, and Unexpected Rearrangement
Bibliographic record
Abstract
The oxidation of allyl selenide 12 with hydrogen peroxide produced the corresponding allyl selenurane 14, the cyclic seleninate ester 4, or the rearranged O-allyl seleninate ester 18, dependng on the conditions. Crossover experiments with selenide 12 and its deuterated crotyl analogue 27 indicated an intramolecular rearrangement that proceeds by an intramolecular pathway where the allyl or crotyl group is translocated via its distal carbon atom to the hydroxymethyl functionality. Variable-temperature NMR experiments with cyclic seleninate ester 4 revealed fluxional behavior at room temperature that was catalyzed by trifluoroacetic acid. Computational studies indicated an activation energy of 12.3 kcal mol(-1) for hydroxyl interchange at selenium, comparable to the value of 15.5 kcal mol(-1) derived from the NMR experiments. The glutathione peroxidase-like activity of 4 was measured in an assay where the catalysis of the reduction of hydrogen peroxide with benzyl thiol was monitored by the appearance of dibenzyl disulfide. The catalytic activity of 4 was double that observed with the unsubstituted seleninate ester 2 but was limited by the competing accumulation of the relatively inert selenenyl sulfide 32, resulting in a deactivation pathway that competes with the primary catalytic cycle.
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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) | 0.002 | 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".