The Role of Specific Amino Acid Residues in The Vibrational Properties of Plastocyanin
Bibliographic record
Abstract
Resonance Raman spectra for zucchini, cucumber, bean, and lettuce plastocyanins, blue copper proteins involved in plant photosynthetic electron transport, have been measured at wavelengths throughout their intense 600-nm absorption band. A comparison of the resonance Raman spectra of these four plastocyanins, and two others previously quantified, demonstrates that they all exhibit vibrational bands with similar frequencies but significantly different relative intensities. Self-consistent analysis of the absorption band and resulting resonance Raman excitation profiles using a time-dependent wave packet formalism for these four plastocyanins demonstrates that many of the derived molecular parameters are similar to those determined previously for two other species of plastocyanin. However, significant differences are observed in the mode-specific displacements and reorganization energies, although the total reorganization energy is 0.16 ± 0.01 eV for all six plastocyanins. A detailed comparison of the structural and compositional differences among the six plastocyanins, using the previously reported structure of poplar a plastocyanin, suggests that these mode-specific differences arise from specific amino acid differences within 10−12 Å of the copper site. These results are interpreted as arising from a through-bond mode-mixing mechanism and a through-space electrostatic mechanism and suggest that the normal modes of the copper site are delocalized into the protein. In addition, lettuce plastocyanin has a significantly greater homogeneous line width, probably as a result of compositional differences adjacent to the copper active site. These results demonstrate that the protein environment is strongly coupled to or mixed in with the copper site vibrational dynamics. Further evidence for the sensitivity of the resonance Raman intensities to particular electron-transfer pathways within the protein is also discussed.
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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".