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Record W2175002727 · doi:10.1021/jo061349t

New Bioorganic Reagents:  Evolved Cyclohexanone MonooxygenaseWhy Is It More Selective?

2006· article· en· W2175002727 on OpenAlexaff
Margaret M. Kayser, Christopher M. Clouthier

Bibliographic record

VenueThe Journal of Organic Chemistry · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsChemistryCyclohexanoneCatalysisMutantResidue (chemistry)MonooxygenaseReagentBioorganic chemistrySubstrate (aquarium)Combinatorial chemistryStereochemistryOrganic chemistryEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Four mutants of the cyclohexanone monooxygenase (CHMO) evolved as catalysts for Baeyer-Villiger oxidation of 4-hydroxycyclohexanone were investigated as catalysts for a variety of 4-substituted and 4,4-disubstituted cyclohexanones. Several excellent catalytic matches (mutant/substrate) were identified. The most important, however, is the finding that, in a number of cases, a mutant with a single exchange, Phe432Ser, was shown to be as robust and more selective as a catalyst than the wild-type CHMO. All biotransformations were performed on a laboratory scale, allowing full characterization of the products. The absolute configurations of two products were established. A model suggesting a possible role of the 432 serine residue in enantioselectivity control is proposed.

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 score0.106
Threshold uncertainty score0.997

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)0.0010.000

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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

Citations42
Published2006
Admission routes1
Has abstractyes

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