Two-Dimensional Infrared Correlation Analysis of Protein Unfolding: Use of Spectral Simulations to Validate Structural Changes during Thermal Denaturation of Bacterial CMP Kinases
Bibliographic record
Abstract
The functional role of bacterial CMP kinases is to recover the energetically exhausted nucleoside monophosphates derived from cell metabolism by transferring a phosphate residue from ATP to CMP or dCMP. These enzymes—important for cell growth and division—possess two distinct binding sites and a number of conserved secondary structure elements. Herein we compare the infrared spectra of two similar, but not identical, CMP kinases from Escherichia coli and Bacillus subtilis. The two-dimensional correlation analysis of the infrared spectra of the two enzymes reveals significant differences in protein structure upon denaturation, a fact possibly linked to their different biochemical and catalytic properties. Model calculations are used to illustrate the effect of two separate processes on the out-of-phase correlation in the two-dimensional (2D) correlation plots. This strategy is then employed to validate the changes observed in the secondary structure of the two enzymes. When bound to the active site of the protein, the two substrates CMP and ATP exert a stabilizing effect on the structure of both proteins; however, the changes observed upon thermal denaturation are different for the two enzymes. Model 2D correlations that simulate the denaturation of the two enzymes confirm the occurrence of temperature-delayed unfolding processes in both proteins. Thermal denaturation and aggregation can be distinguished in both proteins as two distinct processes, separated in time.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".