Predictions of Hydration Free Energies from All-Atom Molecular Dynamics Simulations
Bibliographic record
Abstract
Here, we computed the aqueous solvation (hydration) free energies of 52 small drug-like molecules using an all-atom force field in explicit water. This differs from previous studies in that (1) this was a blind test (in an event called SAMPL sponsored by OpenEye Software) and (2) the test compounds were considerably more challenging than have been used in the past in typical solvation tests of all-atom models. Overall, we found good correlations with experimental values which were subsequently made available, but the variances are large compared to those in previous tests. We tested several different charge models and found that several standard charge models performed relatively well. We found that hypervalent sulfur and phosphorus compounds are not well handled using current force field parameters and suggest several other possible systematic errors. Overall, blind tests like these appear to provide significant opportunities for improving force fields and solvent models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".