Analyzing Protein Folding Cooperativity by Differential Scanning Calorimetry and NMR Spectroscopy
Bibliographic record
Abstract
Some marginally stable proteins undergo microsecond time scale folding reactions that involve significant populations of partly ordered forms, making it difficult to discern individual steps in their folding pathways. It has been suggested that many of these proteins fold non-cooperatively, with no significant barriers to separate the energy landscape into distinct thermodynamic states. Here we present an approach for studying the cooperativity of rapid protein folding with a combination of differential scanning calorimetry (DSC), nuclear magnetic resonance (NMR) relaxation dispersion experiments, and an analysis of the temperature dependence of amide (1)H and (15)N chemical shifts. We applied this method to the PBX homeodomain (PBX-HD), which folds on the microsecond time scale and produces a broad DSC thermogram with an elevated and steeply sloping native-state heat capacity baseline, making it a candidate for barrierless folding. However, by globally fitting the NMR thermal melt and DSC data, and by comparing these results to those obtained from the NMR relaxation dispersion experiments, we show that the native form of the protein undergoes two-state exchange with a small population of the thermally denatured form, well below the melting temperature. This result directly demonstrates the coexistence of distinct folded and unfolded forms and firmly establishes that folding of PBX-HD is cooperative. Further, we see evidence of large-scale structural and dynamical changes within the native state by NMR, which helps to explain the broad and shallow DSC profile. This study illustrates the potential of combining calorimetry with NMR dynamics experiments to dissect mechanisms of protein folding.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".