MétaCan
Menu
Back to cohort
Record W2756573149 · doi:10.1021/acs.iecr.7b02872

Noncovalent Immobilization of Optimized Bacterial Cytochrome P450 BM3 on Functionalized Magnetic Nanoparticles

2017· article· en· W2756573149 on OpenAlexafffund
Atieh Bahrami, Thierry Vincent, Alain Garnier, Faı̈çal Larachi, John Boukouvalas, Maria C. Iliuta

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiocatalysisChemistryHydroxylationCofactorAdsorptionContext (archaeology)EnzymeImmobilized enzymeActive siteCombinatorial chemistryCatalysisOrganic chemistryReaction mechanismBiology

Abstract

fetched live from OpenAlex

A stable insoluble P450 BM3 system that can be easily separated from the reaction medium for recycling, while using less-expensive cofactors (NADH and BNAH) than costly NADPH, can represent a promising biocatalyst in industrial applications. In this context, the present work investigates the immobilization of double mutant cytochrome P450 BM3 (R966D/W1046S) by adsorption and cross-linking-adsorption on Ni 2+ -functionalized magnetic nanoparticles (MNPs). By oxidizing NADH or BNAH, the immobilized BM3 succeeded in hydroxylating the substrates (10- p NCA and myristic acid) to a similar degree as the free enzyme. The adsorbed enzyme showed 88% hydroxylation residual activity after five reaction cycles (five continuous days), which was increased to 100% by cross-linking the adsorbed enzyme. In addition, the cross-linked-adsorbed enzyme kept 41% of its initial activity toward NADH after one month of storage at 4 °C, while the free enzyme showed only 31% residual activity after 1 week and was inactive afterward. The results of this work highlighted that the appropriate choice of the enzyme-support-cofactor system can result in an active, stable, and recyclable biocatalyst, which could attract growing industry interest.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.064
GPT teacher head0.326
Teacher spread0.261 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicEnzyme Catalysis and ImmobilizationFrench-language works237,207