Free Energy Landscape of Protein-like Chains Interacting under Discontinuous Potentials
Bibliographic record
Abstract
The free energy landscape of a protein-like chain is constructed from exhaustive simulation studies using a combination of discontinuous molecular dynamics and parallel tempering methods. The protein model is a repeating sequence of four kinds of monomers, in which hydrogen bond attraction, electrostatic repulsion, and covalent bond vibrations are modeled by step, shoulder and square-well potentials, respectively. These protein-like chains exhibit a helical structure in their folded states. The model allows a natural definition of a configuration by considering which beads are bonded. In the absence of a solvent, the relative free energy of dominant structures is determined from the relative populations, and the probabilities predicted from the calculated free energies are found to be in excellent agreement with the observed probabilities at different temperatures. The free energy landscape of the protein-like chain is analyzed and confirmed to have funnel-like characteristics, confirmed by the fact that the probability of observing the most common configuration approaches unity at low enough temperatures for chains with fewer than 30 beads. The effect on the free energy landscape of an explicit square-well solvent, where the beads that can form intra-chain bonds can also form (weaker) bonds with solvent molecules while other beads are insoluble, is also examined. Simulations for chains of 15, 20 and 25 beads show that at low temperatures, the most likely structures are collapsed helical structures. The temperature at which collapsed helical structures become dominant is higher than in the absence of a solvent. Finally, the dynamics of the protein-like chain immersed in an implicit hard sphere solvent is studied using a simple model in which the implicit solvent interacts on a fast time scale with the chain beads and provides sufficient friction so that the motion of monomers is governed by the Smoluchowski equation. Using a Markovian model of the kinetics of transitions between conformations, the equilibration process from an ensemble of initially extended configurations to mainly folded configurations is investigated at low effective temperatures for a number of different chain lengths. It was observed that folding profiles appear to be single exponentials and independent of temperature at low temperatures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".