Reduction Potentials of Rieske Clusters: Importance of the Coupling between Oxidation State and Histidine Protonation State
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Bibliographic record
Abstract
Rieske [2Fe-2S] clusters can be classified into two groups, depending on their reduction potentials. Typical high-potential Rieske proteins have pH-dependent reduction potentials between +350 and +150 mV at pH 7, and low-potential Rieske proteins have pH-independent potentials of around -150 mV at pH 7. The pH dependence of the former group is attributed to coupled deprotonation of the two histidine ligands. Protein-film voltammetry has been used to compare three Rieske proteins: the high-potential Rieske proteins from Rhodobacter sphaeroides (RsRp) and Thermus thermophilus (TtRp) and the low-potential Rieske ferredoxin from Burkholderia sp. strain LB400 (BphF). RsRp and TtRp differ because there is a cluster to serine hydrogen bond in RsRp, which raises its potential by 140 mV. BphF lacks five hydrogen bonds to the cluster and an adjacent disulfide bond. Voltammetry measurements between pH 3 and 14 reveal that all the proteins, including BphF, have pH-dependent reduction potentials with remarkably similar overall profiles. Relative to RsRp and TtRp, the potential versus pH curve of BphF is shifted to lower potential and higher pH, and the pK(a) values of the histidine ligands of the oxidized and reduced cluster are closer together. Therefore, in addition to simple electrostatic effects on E and pK(a), the reduction potentials of Rieske clusters are determined by the degree of coupling between cluster oxidation state and histidine protonation state. Implications for the mechanism of quinol oxidation at the Q(O) site of the cytochrome bc(1) and b(6)f complexes are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it