A theoretical analysis on hydration thermodynamics of proteins
Bibliographic record
Abstract
The hydration free energy (HFE) of several proteins modeled using the all-atom force field is calculated by employing the three-dimensional reference interaction site model theory, a recently developed integral equation theory of molecular solvation. The HFE is decomposed into the energetic and entropic components under the isochoric condition. The former comprises the protein-water interaction energy and the water reorganization energy arising from the structural changes induced in water. Each component is further decomposed into the nonelectrostatic and electrostatic contributions. It is found that the HFE is governed by the nonelectrostatic hydration entropy and the electrostatic hydration energy. The nonelectrostatic hydration entropy is almost exclusively ascribed to the translational entropy loss of water upon the protein insertion. It asymptotically becomes proportional to the excluded volume (EV) for water molecules as the protein size increases. The hydration energy is determined by the protein-water interaction energy which is half compensated by the water reorganization energy. These energy terms are approximately proportional to the water-accessible surface area (ASA). The energetic and entropic contributions are balanced with each other and the HFE has no apparent linear relation with the EV and ASA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".