Hydrophobic association and solvation of neopentane in Urea, TMAO and Urea-TMAO solution
Bibliographic record
Abstract
A detailed knowledge on hydrophobic association and solvation is crucial in understanding the con-formational stability of proteins and polymers in osmolyte solutions. Using Molecular Dynamics simulations, we found the hydrophobic association using neopentane molecules is greater in mixed urea-TMAO-water solution in comparison to that in 8 M urea solution, in 4 M TMAO solution and in neat water. The neopentane association in urea solution is greater than that in TMAO solution or neat water. We find the association is even less in TMAO solution than pure water. From free ener-gy calculations, it is revealed that the neopentane sized cavity creation in mixed urea-TMAO-water is most unfavorable and that causes the highest hydrophobic association. The cavity formation in urea solution is either more unfavorable or comparable to that in TMAO solution. Importantly, it is found that the population of neopentane-neopentane contact pair and the free energy contribution for cavity formation step in TMAO solution are very sensitive towards the choice of TMAO force-fields. A careful construction of TMAO force-fields is important for studying hydrophobic associa-tion. Interestingly it is observed that the total solute-solvent dispersion interaction energy contribu-tion is always most favorable in mixed urea-TMAO-water. The magnitude of this interaction energy is greater in urea solution relative to TMAO solution for two different force-fields of TMAO, whereas the lowest value is obtained in pure water. It is revealed that the extent of the overall hy-drophobic association in osmolyte solutions is mainly governed by the cavity creation step and it nullifies the contribution comes from the solute-solvent interaction contribution.
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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) | 0.002 | 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".