A Charge Moving Algorithm for Molecular Dynamics Simulations of Gas-Phase Proteins
Bibliographic record
Abstract
A method for moving charges in a coarse-grained simulation of gas-phase proteins is presented which uses a Monte Carlo approach to move charges between charge sites. The method is used to study the role of charge movement in the dissociation mechanism of protein complexes in order to better understand experimentally observed mass spectra from CID studies. The charge hopping process is analyzed using energy distributions and a pair correlation plot. Hopping rates, charge distributions, and structural parameters (radius of gyration and RMSD) are also calculated. The importance of charge movement for the unfolding of protein complexes is demonstrated. The algorithm is implemented in the GROMACS molecular dynamics software package. In this study, transthyretin (TTR) tetramer is used with the MARTINI force field as a model system, and comparisons to experiments are made. The hopping and unfolding are found to be controlled by the Coulomb repulsion among the charges in the complex.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".