Improved Angle Potentials for Coarse-Grained Molecular Dynamics Simulations
Bibliographic record
Abstract
Potentials routinely used in atomistic molecular dynamics simulations are not always suitable for modeling systems at coarse-grained resolution. For example, in the calculation of traditional torsion angle potentials, numerical instability is often encountered in the case of very flexible molecules. To improve the stability and accuracy of coarse-grained molecular dynamics simulations, we propose two approaches. The first makes use of improved forms for the angle potentials: the restricted bending (ReB) potential prevents torsion angles from visiting unstable or unphysical configurations and the combined bending-torsion (CBT) potential smoothly flattens the interactions when such configurations are sampled. In the second approach, dummy-assisted dihedral (DAD), the torsion potential is applied differently: instead of acting directly on the beads, it acts on virtual beads, bound to the real ones. For simple geometrical reasons, the unstable region is excluded from the accessible conformational space. The benefits of the new approaches are demonstrated in simulations of polyethylene glycol (PEG), polystyrene (PS), and polypeptide molecules described by the MARTINI coarse-grained force field. The new potentials are implemented in an in-house version of the Gromacs package, publicly available.
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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 | 0.006 |
| 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 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".