The Influence of pH on Long-Range Electron Transfer and Proton-Coupled Electron Transfer in Ruthenium-Modified Azurin
Bibliographic record
Abstract
Long-range electron transfer (ET) is an essential component of all biological systems. Reactions of metalloproteins are important in this context. Recent work on protein “charge ladders” has revealed how the redox state of embedded metal ions can influence the ionization of amino acid residues at protein surface sites. Inspired by these observations, we carried out a variable pH investigation of intramolecular ET reactions in a ruthenium-modified protein system built on azurin from Pseudomonas aeruginosa. We also generate a Pourbaix diagram that describes the variable pH redox behavior of a Ru model complex, Ru(2,2′-bipyridyl)2(imidazole)2(PF6)2. The intramolecular ET rate constants for the oxidation of azurin-Cu+ by flash-quench-generated Ru3+ oxidants do not follow the predictions of the semi-classical ET rate expression with fixed values of reorganization energy (λ) and electronic coupling (HDA). Based on the pH dependence of the Ru3+/2+ redox couple, we propose a model where pure ET is operative at acidic pH values (≤ 7) and the mechanism changes to proton-coupled electron transfer at pH ≥ 7.5. The implications of this mechanistic proposal are discussed in the context of biological redox reactions and with respect to other examples of intramolecular ET reactions in the literature.
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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) | 0.001 | 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".