Spatial Decomposition Analysis of the Thermodynamics of Cyclodextrin Complexation
Bibliographic record
Abstract
We propose a method of spatial decomposition analysis (SDA) to study the thermodynamics of association in solution, based on three-dimensional molecular theory of solvation. We decompose the solvation thermodynamics quantities into the excluded volume and solvation shell terms and further break them down into partial contributions of the functional groups of the associating species. For illustration, we applied the SDA method to the complexation of β-cyclodextrin and 1-adamantanecarboxylic acid in water. We calculated the changes in the free energy and in the partial molar volume upon the association and decomposed them into the partial contributions of the functional groups to the excluded volume and solvation shell terms. The SDA shows that the adamantyl group of 1-adamantanecarboxylic acid is responsible for the complexation more than its carboxyl group and that the carboxyl has little contribution to the association process. The SDA results are in good agreement with the observation made in a recent molecular dynamics simulation. The SDA method can reveal a microscopic picture for association processes in solution in a number of areas, including protein stability, and might be a useful tool for rational drug design.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".