Intramolecular Electron Transfer versus Substrate Oxidation in Lactoperoxidase: Investigation of Radical Intermediates by Stopped-Flow Absorption Spectrophotometry and (9−285 GHz) Electron Paramagnetic Resonance Spectroscopy
Bibliographic record
Abstract
We have combined the information obtained from rapid-scan electronic absorption spectrophotometry and multifrequency (9−295 GHz) electron paramagnetic resonance (EPR) spectroscopy to unequivocally determine the electronic nature of the intermediates in milk lactoperoxidase as a function of pH and to monitor their reactivity with organic substrates selected by their different accessibilities to the heme site. The aim was to address the question of the putative catalytic role of the protein-based radicals. This experimental approach allowed us to discriminate between the protein-based radical intermediates and [Fe(IV)═O] species, as well as to directly detect the oxidation products by EPR. The advantageous resolution of the g anisotropy of the Tyr • EPR spectrum at high fields showed that the tyrosine of the [Fe(IV)═O Tyr • ] intermediate has an electropositive and pH-dependent microenvironment [ g x value of 2.0077(0) at pH ≥ 8.0 and 2.0066(2) at 4.0 ≤ pH ≤ 7.5] possibly related to the radical stability and function. Two types of organic molecules (small aromatic vs bulkier substrates) allowed us to distinguish different mechanisms for substrate oxidation. [Fe(IV)═O Por •+ ] is the oxidizing species of benzohydroxamic acid, o -dianisidine, and o -anisidine via a heme-edge reaction and of mitoxantrone via a long-range electron transfer (favored at pH 8) not involving the tyrosyl radical, the formation of which competed with the substrate oxidation at pH 5. In contrast, the very efficient reaction with ABTS at pH 5 is consistent with [Fe(IV)═O Tyr • ] being the oxidizing species. Accordingly, the identification of the ABTS binding site by X-ray crystallography may be a valuable tool in rational drug design.
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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 | 0.001 |
| 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 | 0.001 |
| 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".