Effects of desolvation barriers and sidechains on local–nonlocal coupling and chevron behaviors in coarse-grained models of protein folding
Bibliographic record
Abstract
Local-nonlocal coupling is an organizational principle in protein folding. It envisions a cooperative energetic interplay between local conformational preferences and favorable nonlocal contacts. Previous theoretical studies by our group showed that two classes of native-centric coarse-grained models can capture the experimentally observed high degrees of protein folding cooperativity and diversity in folding rates. These models either embody an explicit local-nonlocal coupling mechanism or incorporate desolvation barriers in the models' pairwise interactions. Here a conceptual connection is made between these two paradigmatic coarse-grained interaction schemes by showing that desolvation barriers enhance local-nonlocal coupling. Furthermore, we find that a class of coarse-grained protein models with a single-site representation of sidechains also increases local-nonlocal coupling relative to mainchain models without sidechains. Enhanced local-nonlocal coupling generally leads to higher folding cooperativity and chevron plots with more linear folding arms. For the sidechain models studied, the chevron plot simulated with entirely native-centric intrachain interactions behaves very similarly to the corresponding chevron plots simulated with interactions that are partly modulated by sequence- and denaturant-dependent transfer free energies. In these essentially native-centric models, the mild chevron rollovers in the simulated folding arm are caused by occasionally populated intermediates as well as the movement of the unfolded and putative folding transition states. The strength and limitation of the models are analyzed by comparison with experiment. New formulations of sidechain models that may provide a physical account for nonnative interactions are also explored.
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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".