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Record W2091727807 · doi:10.1002/elsc.200700052

Enhanced Asymmetric Reduction of Ethyl 3‐Oxobutyrate by Baker's Yeast via Substrate Feeding and Enzyme Inhibition

2008· article· en· W2091727807 on OpenAlexaff
Kam Loon Fow, Lester Chi-Heng Poon, Seon-Mi Sim, Gaik‐Khuan Chuah, Stephan Jaenicke

Bibliographic record

VenueEngineering in Life Sciences · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsUniversity of British Columbia
FundersNational University of SingaporeLee Foundation
KeywordsYeastSubstrate (aquarium)ChemistryEnzymeEnantiomeric excessBiocatalysisEthyl acetateFermentationStereochemistryBiochemistryEnantioselective synthesisCatalysisBiologyReaction mechanism

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.206
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2008
Admission routes1
Has abstractyes

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