Determination of the Fe−CO Bond Energy in Myoglobin Using Heterodyne-Detected Transient Thermal Phase Grating Spectroscopy
Bibliographic record
Abstract
The bond energies at active sites of proteins are intimately coupled to the structure-function relationship in biological systems. Due to the unknown nature of the protein relaxation along a reaction coordinate, it has not been possible to directly determine bond energies relevant to protein function. By embedding proteins in trehalose glasses, it is possible to freeze out protein relaxation on short time scales and determine the bond energies of photolabile ligands using photothermal spectroscopies. As a prototypical example, the photodissociation dynamics and energetics of carboxy-myoglobin (MbCO) in a trehalose glass matrix at room temperature were studied by transient absorption (or pump-probe) and transient thermal phase grating spectroscopy to determine the CO recombination dynamics and associated energetics, respectively. Both the initial energetics of the bond breaking and the energy released upon bond reformation could be used, on a time scale faster than significant protein relaxation, to determine the Fe-CO bond energy as 34 +/- 4 kcal/mol. This bond energy is significantly larger than that typically cited (25 kcal/mol) on the basis of indirect measurements but is in good agreement with recent theoretical predictions (35 kcal/mol) (Rovira, C.; Parrinello, M. Int. J. Quantum Chem. 2000, 80, 1172). This result in combination with the theoretical study suggests that protein structure plays a significant role in the bond energies at active sites which in turn provides a tuning element of the effective barrier heights independent to the transition state region.
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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) | 0.000 | 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 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".