Computer Simulation of the Distribution of Hexane in a Lipid Bilayer: Spatially Resolved Free Energy, Entropy, and Enthalpy Profiles
Bibliographic record
Abstract
The partitioning behavior of small molecules in lipid bilayers is important in a variety of areas including membrane protein folding and pharmacology. However, the inhomogeneous nature of lipid bilayers on a nanometer length scale complicates experimental studies of membrane partitioning. To gain more insight in the partitioning of a small molecule into the lipid bilayer, we have carried out atomistic computer simulations of hexane in a dioleoyl phosphatidylcholine model membrane. We have been able to obtain spatially resolved free energy, entropy, enthalpy, and heat capacity profiles based on umbrella sampling calculations at three different temperatures. In agreement with experiment, hexane partitions preferentially to the center of the bilayer. This process is driven almost entirely by a favorable entropy change, consistent with the hydrophobic effect. In contrast, partitioning to the densest region of the acyl chains is dominated by a favorable enthalpy change with a small entropy change, which is consistent with the "nonclassical" hydrophobic effect or "bilayer" effect. We explain the features of the entropy and enthalpy profiles in terms of density and free volume in the system.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".