Folding free energy landscapes of <i>β</i>-sheets with non-polarizable and polarizable CHARMM force fields
Bibliographic record
Abstract
Molecular dynamics (MD) simulations of peptides and proteins offer atomic-level detail into many biological processes, although the degree of insight depends on the accuracy of the force fields used to represent them. Protein folding is a key example in which the accurate reproduction of folded-state conformations of proteins and kinetics of the folding processes in simulation is a longstanding goal. Although there have been a number of recent successes, challenges remain in capturing the full complexity of folding for even secondary-structure elements. In the present work, we have used all-atom MD simulations to study the folding properties of one such element, the C-terminal β-hairpin of the B1 domain of streptococcal protein G (GB1). Using replica-exchange umbrella sampling simulations, we examined the folding free energy of two fixed-charge CHARMM force fields, CHARMM36 and CHARMM22*, as well as a polarizable force field, the CHARMM Drude-2013 model, which has previously been shown to improve the folding properties of α-helical peptides. The CHARMM22* and Drude-2013 models are in rough agreement with experimental studies of GB1 folding, while CHARMM36 overstabilizes the β-hairpin. Additional free-energy calculations show that small adjustments to the atomic polarizabilities in the Drude-2013 model can improve both the backbone solubility and folding properties of GB1 without significantly affecting the model’s ability to properly fold α-helices. We also identify a non-native salt bridge in the β-turn region that overstabilizes the β-hairpin in the C36 model. Finally, we demonstrate that tryptophan fluorescence is insufficient for capturing the full β-hairpin folding pathway.
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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".