Electronic Structure Contributions to Electron-Transfer Reactivity in Iron−Sulfur Active Sites: 3. Kinetics of Electron Transfer
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Bibliographic record
Abstract
The kinetics of electron transfer for rubredoxins are examined using density functional methods to determine the electronic structure characteristics that influence and allow for fast electron self-exchange in these electron-transport proteins. Potential energy surfaces for [FeX(4)](2-,1-) models confirm that the inner-sphere reorganization energy is inherently small for tetrathiolates ( approximately 0.1 eV), as evidenced by the only small changes in the equilibrium Fe-S bond distance during redox (Deltar(redox) approximately 0.05 A). It is concluded that electronic relaxation and covalency in the reduced state allow for this small in this case relative to other redox couples, such as the tetrachloride. Using a large computational model to include the protein medium surrounding the [Fe(SCys)(4)](2-,1-) active site in Desulfovibrio vulgaris Rubredoxin, the electronic coupling matrix element for electron self-exchange is defined for direct active-site contact (H0(DA)). Simple Beratan-Onuchic model is used to extend coupling over the complete surface of the protein to provide an understanding of probable electron-transfer pathways. Regions of similar coupling properties are grouped together to define a surface coupling map, which reveals that very efficient self-exchange occurs only within 4 sigma-bonds of the active site. Longer-range electron transfer cannot support the fast rates of electron self-exchange observed experimentally. Pathways directly through the two surface cysteinate ligands dominate, but surface-accessible amides hydrogen-bonded to the cysteinates also contribute significantly to the rate of electron self-exchange.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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