Enhanced Asymmetric Reduction of Ethyl 3‐Oxobutyrate by Baker's Yeast via Substrate Feeding and Enzyme Inhibition
Bibliographic record
Abstract
Abstract The moderate enantioselectivity of wild form baker's yeast can be considerably increased either by using continuous feeding to maintain a low substrate concentration throughout the reaction, or by the selective inhibition of competing enzymatic pathways. The reduction of ethyl 3‐oxobutyrate to ethyl (S)‐3‐hydroxybutyrate was used as a model reaction. With the substrate feeding method, the enantioselectivity could be increased from 75 % to as high as 98 %. The increased selectivity originates from the much higher substrate binding constant of the (R)‐specific enzymes, so that these enzymes remain essentially inactive if a low concentration of ethyl 3‐oxobutyrate is maintained in the bioreactor. Alternatively, the enantioselectivity of baker's yeast can be improved by selectively blocking competing enzymatic pathways. It was found that vinyl acetate is a selective inhibitor for the (R)‐specific enzymes. Ethyl (S)‐3‐hydroxybutyrate with an enantiomeric excess of 98 % was obtained by pre‐incubation of baker's yeast in 100 mM of vinyl acetate solution for 1 h. These results suggest that by selecting appropriate process conditions, natural baker's yeast can be a competitive biocatalyst for the large‐scale production of chiral secondary alcohols.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".