Protein Denaturation in Vacuo. Behavior of the Four-α-Helix Bundle of Apocytochrome <i>c</i><i>‘</i> under Centrifugal Unfolding Conditions
Bibliographic record
Abstract
Experiments and simulations on dry proteins in a low-pressure gas suggest that unfolding and refolding transitions are possible even in the absence of water. Here, we use computer simulations of molecular dynamics to gain further insight into the microscopic mechanisms underlying protein denaturation in vacuo. Recent studies of neutral lysozyme provide an initial guide into the principles at play during the in vacuo unfolding of a multidomain protein. In this work, we contrast its behavior with that of cytochrome c ‘; this protein has the same chain length as lysozyme, but it is organized as a four-α-helix bundle. Using an ensemble of molecular dynamics trajectories for cytochrome c ‘, we discuss the qualitative response that follows the imposition of unfolding conditions. The unfolding bias is caused by small, yet systematic, “centrifugal” forces associated with unrestrained spinning in vacuo. The emerging mechanisms appear to depend on the native fold. Whereas lysozyme exhibits a fast denaturing transition, cytochrome c ‘ exhibits restricted deformations within the same time scale. Two characteristic behaviors are found. In the more common response, the protein undergoes a limited reduction in secondary structure, and relaxation leads back to quasi-native states. In the less common response, cytochrome c ‘ unfolds partially by losing compactness and tertiary contacts in a correlated manner. Our approach illustrates the usefulness of centrifugal unfolding in vacuo as a tool to detect large-scale configurational motions accessible to the native state. The method provides insight into (a) possible pathways associated with the initial steps of unfolding and (b) a qualitative survey of regions of configurational space connecting the native state attractor with the denatured “state”. In this regard, we show for the first time how the same denatured “state” can be reached not only by direct unfolding of the native state but also by re-unfolding of partly folded intermediates.
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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 | 0.000 | 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) | 0.001 | 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".