Dynamic Docking and Electron-Transfer between Cytochrome<i> b</i><sub>5</sub> and a Suite of Myoglobin Surface-Charge Mutants. Introduction of a Functional-Docking Algorithm for Protein−Protein Complexes
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Bibliographic record
Abstract
Horse myoglobin (Mb) provides a convenient "workbench" for probing the effects of electrostatics on binding and reactivity in the dynamic [Mb, cytochrome b(5)] electron-transfer (ET) complex. We have combined mutagenesis and heme neutralization to prepare a suite of six Mb surface-charge variants: the [S92D]Mb and [V67R]Mb mutants introduce additional charges on the "front" face, and incorporation of the heme di-ester into each of these neutralizes the charge on the heme propionates which further increases the positive charge on the "front" face. For this set of mutants, the nominal charge of Mb changes by -1 to +3 units relative to that for native Mb. For each member of this set, we have measured the bimolecular quenching rate constant (k(2)) for the photoinitiated (3)ZnDMb --> Fe(3+)b(5) ET reaction as a function of ionic strength. We find: (i) a dramatic decoupling of binding and reactivity, in which k(2) varies approximately 10(3)-fold within the suite of Mbs without a significant change in binding affinity; (ii) the ET reaction occurs within the "thermodynamic" or "rapid exchange" limit of the "Dynamic Docking" model, in which a large ensemble of weakly bound protein-protein configurations contribute to binding, but only a few are reactive, as shown by the fact that the zero-ionic-strength bimolecular rate constant varies exponentially with the net charge on Mb; (iii) Brownian dynamic docking profiles allow us to visualize the microscopic basis of dynamic docking. To describe these results we present a new theoretical approach which mathematically combines PATHWAY donor/acceptor coupling calculations with Poisson-Boltzmann-based electrostatics estimates of the docking energetics in a Monte Carlo (MC) sampling framework that is thus specially tailored to the intermolecular ET problem. This procedure is extremely efficient because it targets only the functionally active complex geometries by introducing a "reactivity filter" into the computations themselves, rather than as a subsequent step. This efficiency allows us to employ more computationally expensive and accurate methods to describe the relevant intermolecular interaction energies and the protein-mediated donor/acceptor coupling interactions. It is employed here to compute the changes in the bimolecular rate constant for ET between Mb and cyt b(5) upon variations in the myoglobin surface charge, pH, and ionic strength.
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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