Studies of selective chemical catalysis by hydrolases
Bibliographic record
Abstract
Hydrolase catalyzed reactions are used for selective chemical catalysis. With directed evolution, rational mutations and molecular modeling the selectivity of these hydrolases can be increased and the origin of selectivity determined. This study investigates four selective hydrolase catalyzed reactions. Using molecular modeling the unusual regioselectivity of Pseudomonas cepacia lipase (PCL) and the selectivity of Candida antarctica B lipase (CAL-B) in nucleoside acylation reactions has been attributed to the binding of the nucleoside base within the active site. The enantio-selectivity of Pseudomonas fluorescens esterase (PFE) has been improved using a rational approach to directed evolution and models to explain the origin of improved mutants has been produced. The enantioselectivity of the beta-lactam ring opening reaction by CAL-B has been attributed to unfavorable steric interaction of the substrate with Ile189 and a model has been proposed for an alcohol bridge between the catalytic histidine (His224) and the lactam amine. Finally, high acetyl selectivity of ThermoGen esterase E018b has been demonstrated and reaction conditions optimized.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".