Proteins <i>in vacuo</i>: Denaturing and folding mechanisms studied with computer‐simulated molecular dynamics
Why this work is in the frame
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Bibliographic record
Abstract
Abstract I. Introduction 402 II. Experiments and Simulations: Background 403 III. Unfolding Studies 406 A. Centrifugal Unfolding of Neutral Proteins 407 B. Unfolding by Coulombic Repulsion 409 C. Unfolding by Screened van der Waals Attraction 411 IV. Refolding Studies 412 V. Closing Remarks 414 VI. Acknowledgments 415 Appendix 1. Molecular Shape Descriptors for Protein Backbones 416 Appendix 2. MD Simulations 417 References 419 Mounting evidence from experiments suggests that the native fold in solution is metastable in dehydrated proteins. Results from a number of experiments that use mass spectrometry indicate also that folding–unfolding transitions take place in protein ions even in the absence of water. These observations on anhydrous proteins call for a re‐evaluation of our understanding of the folding transition. In this context, computer‐assisted simulations are an important complementary tool. Here, we provide an overview of recent progress on the simulation of proteins in vacuo . In particular, we discuss the response of proteins and protein ions to perturbations that trigger unfolding and re‐folding transitions. By comparing the general patterns emerging from theory and experiment, we propose a series of new measurements that could help to validate, and improve, current simulation models. © 2002 Wiley Periodicals, Inc., Mass Spec Rev 20:402–422, 2001; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/mas.10012
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it