Computer simulation study of folding thermodynamics and kinetics of proteins in osmolytes and denaturants
Bibliographic record
Abstract
In living cells, the presence of macromolecular crowders, such as osmolytes or denaturants, strongly affects the stability of folded proteins. The overall effects depend on the size, concentration, and chemical properties of the crowding agents. This work uses an all-atom Gō model of the Trp-cage in spherical solvents to probe the physical origin of protein stabilization/destabilization by osmolytes/denturants. The solvent quality is controlled by the solvent-protein contact εPS that can represent repulsive osmolytes (εPS > 0) or attractive denaturants (εPS < 0). The model is used to show that protein stabilization by osmolytes proceeds by an excluded volume, entropy-driven mechanism. Protein destabilization by denaturant is shown to be driven by changes in enthalpy. It is found that small osmolytes are the most effective stabilizer of proteins. Folding simulations of the Trp-cage in osmolytes observe a two-fold increase in folding rates, for small osmolytes. This is due to an osmolyte-induced shift to more compact unfolded protein conformations.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".