The hydration structure of methylthiolate from QM/MM molecular dynamics
Bibliographic record
Abstract
Thiols are widely present in biological systems, most notably as the side chain of cysteine amino acids in proteins. Thiols can be deprotonated to form a thiolate which affords a diverse range of enzymatic activity and modes for chemical modification of proteins. Parameters for modeling thiolates using molecular mechanical force fields have not yet been validated, in part due to the lack of structural data on thiolate solvation. Here, the CHARMM36 and Amber models for thiolates in aqueous solutions are assessed using free energy perturbation and hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations. The hydration structure of methylthiolate was calculated from 1 ns of QM/MM MD (PBE0-D3/def2-TZVP//TIP3P), which shows that the water–S− distances are approximately 2 Å with a coordination number near 6. The CHARMM thiolate parameters predict a thiolate S radius close to the QM/MM value and predict a hydration Gibbs energy of −329.2 kJ/mol, close to the experimental value of −318 kJ/mol. The cysteine thiolate model in the Amber force field underestimates the thiolate radius by 0.2 Å and overestimates the thiolate hydration energy by 119 kJ/mol because it uses the same Lennard-Jones parameters for thiolates as for thiols. A recent Drude polarizable model for methylthiolate with optimized thiolate parameters also performs well. SAPT2+ [Symmetry Adapted Perturbation Theory (SAPT)] analysis indicates that exchange repulsion is larger for the methylthiolate, consistent with it having a more diffuse electron density distribution in comparison with the parent thiol. These data demonstrate that it is important to define distinct non-bonded parameters for the protonated/deprotonated states of amino acid side chains in molecular mechanical force fields.
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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".