A heme•DNAzyme activated by hydrogen peroxide catalytically oxidizes thioethers by direct oxygen atom transfer rather than by a Compound I-like intermediate
Bibliographic record
Abstract
Hemin [Fe(III)-protoporphyrin IX] is known to bind tightly to single-stranded DNA and RNA molecules that fold into G-quadruplexes (GQ). Such complexes are strongly activated for oxidative catalysis. These heme•DNAzymes and ribozymes have found broad utility in bioanalytical and medicinal chemistry and have also been shown to occur within living cells. However, how a GQ is able to activate hemin is poorly understood. Herein, we report fast kinetic measurements (using stopped-flow UV-vis spectrophotometry) to identify the H2O2-generated activated heme species within a heme•DNAzyme that is active for the oxidation of a thioether substrate, dibenzothiophene (DBT). Singular value decomposition and global fitting analysis was used to analyze the kinetic data, with the results being consistent with the heme•DNAzyme's DBT oxidation being catalyzed by the initial Fe(III)heme-H2O2 complex. Such a complex has been predicted computationally to be a powerful oxidant for thioether substrates. In the heme•DNAzyme, the DNA GQ enhances both the kinetics of formation of the active intermediate as well as the oxidation step of DBT by the active intermediate. We show, using both stopped flow spectrophotometry and EPR measurements, that a classic Compound I is not observable during the catalytic cycle for thioether sulfoxidation.
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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".