An Investigation of the Influence of Tyrosine Local Interactions on Electron Hopping in a Model Protein
Bibliographic record
Abstract
Multi-step electron transfer reactions are important to the function of many cellular systems. The ways in which such systems have evolved to direct electrons along specific pathways are largely understood, but less so are the ways in which the reduction–oxidation potentials of individual redox sites are controlled. We prepared a series of three new artificial variants of Pseudomonas aeruginosa azurin where a tyrosine (Tyr109) is situated between the native Cu ion and a Ru(II) photosensitizer tethered to a histidine (His107). Arginine, glutamine, or methionine were introduced as position 122, which is near to Tyr109. We investigated the rate of CuI oxidation by a flash-quench generated Ru(III) oxidant over pH values from 5 to 9. While the identity of the residue at position 122 affects some of the physical properties of Tyr109, the rates of CuI oxidation are only weakly dependent on the identity of the residue at 122. The results highlight that more work is still needed to understand how non-covalent interactions of redox active groups are affected in redox proteins.
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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".