Halothane Solvation in Water and Organic Solvents from Molecular Simulations with New Polarizable Potential Function
Bibliographic record
Abstract
The partitioning of a substrate from one phase into another is a complex process with widespread applications: from chemical technology to the pharmaceutical industry. One particularly well-known and well-studied example is 2-bromo-2-chloro-1,1,1-trifluoroethane (halothane) trafficking through the lipid bilayer. Halothane is a model volatile anesthetic known to impact functions of model lipid bilayers, altering the structure and thickness upon its partitioning from the bulk phase. A number of theoretical and experimental investigations suggest the importance of electronic polarizability, determining a preference for halothane to partition in the interfacial systems as in lipid bilayers or binary solvents. The recently published protocol for the development of polarizable force fields based on the classical Drude model has provided fresh impetus to efforts directed at understanding the molecular principles governing complex thermodynamics of the hydrophobic hydration. Here, molecular simulations were combined with free energy simulations to study solvation of halothane in polarizable water and methanol. The absolute free energy of halothane solvation in different solvents (water, methanol, and n-hexane) has been evaluated for additive and polarizable models. It was found that both additive and polarizable models provide an adequate description of the halothane solvation in high-dielectric (polar) solvents such as water, but explicit accounting for electronic polarization is imperative for a correct description of the solvation thermodynamics in nonpolar systems. To study halothane dynamics in binary mixtures, all-atom molecular dynamics (MD) simulations for halothane-methanol mixtures in a wide range of concentrations were performed alongside an analysis of structural organization, dynamics, and thermodynamic properties to dissect the molecular determinants of the halothane solvation in polar and amphiphilic liquids such as methanol. Additionally, a theoretical test of the hypothesis on the weak hydrogen bonding of halothane and methanol in the condensed phase is provided, which was presented on the basis of spectroscopic analysis of the C-H vibrations in different gas-phase complexes. The simulations performed in the condensed phase suggest that hydrophobic interactions between halothane and methanol play a dominant role in preferential solvation.
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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) | 0.001 | 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 | 0.002 | 0.001 |
| 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".