A QM/MM investigation of the catalytic mechanism of acetylene hydratase: insights into engineering a more effective enzyme
Bibliographic record
Abstract
In the present investigation, a QM/MM approach was used to better understand the effect of the second environmental shell of the active site on the catalytic conversion of acetylene to acetaldehyde by acetylene hydratase (AH). In addition, the effect of substituting W-coordinating sulfur atoms with selenium atoms was done to provide insight into the influence of the W-coordinating atoms on the catalytic reaction. From the results, it found that the presence of the second shell environment had a significant effect on the reaction. Specifically, in the absence of the MM second shell environment (i.e., QM-cluster model), the rate-determining step is defined by the first proton transfer step. In contrast, for the QM/MM model, the rate-determining step is defined by the water attacking step. Moreover, with the presence of the MM second shell environment, a key intermediate found in the DFT-cluster investigation does not exist in the QM/MM investigation. Rather, what was a two-step process in the DFT-cluster study was calculated to occur in a single step for the QM/MM study. Regarding the sulfur to selenium substitutions, it was found that Gibbs energy for the acetylene binding phase was significantly affected. Notably, the trans-position selenium made the binding of acetylene 65.6 kJ mol −1 less endergonic. Moreover, the overall reaction became 38.2 kJ mol −1 less endergonic compared with the wild type (WT) AH model. Thus, the substitution of key W-coordinating sulfur atoms with selenium atoms may offer a means to enhance the catalytic mechanism of AH considerably.
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 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".