Anti-cooperativity in hydrophobic interactions: A simulation study of spatial dependence of three-body effects and beyond
Bibliographic record
Abstract
To better understand the energetics of hydrophobic core formation in protein folding under ambient conditions, the potential of mean force (PMF) for different three-methane configurations in an aqueous environment is computed by constant-pressure Monte Carlo sampling using the TIP4P model of water at 25 °C under atmospheric pressure. Whether the hydrophobic interaction is additive, cooperative or anti-cooperative is determined by whether the directly simulated three-methane PMF is equal to, more favorable, or less favorable than the sum of two-methane PMFs. To ensure that comparisons between PMFs are physically meaningful, a test-particle insertion technique is employed to provide unequivocal correspondence between zero PMF value and the nonexistent inter-methane interaction (zero reference-state free energy) experienced by a pair of methanes infinitely far apart. Substantial deviations from pairwise additivity are observed. Significantly, a majority of the three-methane configurations investigated exhibit anti-cooperativity. Previously simulated three-methane PMFs were defined along only one single coordinate. In contrast, our technique enables efficient computation of a three-methane PMF that depends on two independent position variables. The new results show that the magnitude and sign of nonadditivity exhibit a prominent angular dependence, highlighting the complexity of multiple-body hydrophobic interactions. Packing consideration of crystal-like constructs of an infinite number of methanes and analysis of methane sublimation and hydration data suggest that anti-cooperativity may be a prevalent feature in hydrophobic interactions. Ramifications for protein folding are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".