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Record W4410326662 · doi:10.1021/acs.langmuir.5c00874

Lipase-Catalyzed Michael Addition in ‘Water-like’ Ionic Liquids and Tertiary Amides: What Is the Role of the Enzymes?

2025· article· en· W4410326662 on OpenAlexaff
Hua Zhao, Angira Roy, Ashen Samaranayake, Piyuni Ishtaweera, Gary A. Baker, Leo G. Markmann, N. S. Fernando, Katie R. Mitchell‐Koch

Bibliographic record

VenueLangmuir · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsUniversity of Manitoba
FundersNational Science Foundation
KeywordsLipaseMichael reactionCatalysisIonic liquidChemistryEnzymeOrganic chemistryIonic bondingEnzyme catalysisPolymer chemistry

Abstract

fetched live from OpenAlex

Michael addition is an important reaction to form C–C bonds. Different hydrolases (e.g., lipases, proteases, and d -aminoacylase) have been reported to catalyze C–C-forming reactions, but the reaction mechanism is not entirely clear. This study examined several model Michael reactions catalyzed by lipases and amino acids in various solvents and found that “water-like” functionalized ionic liquids (ILs) increased the reaction yield to 35–55% from 30% in triglyme and 17% in [BMIM][Tf 2 N]. Interestingly, tertiary amides as solvents remarkably increased the reaction yield (to up to 65–85%) and enantioselectivity (up to 71–84% ee ) when catalyzed by porcine pancreatic lipase (PPL). Our experimental, spectroscopic, and computational studies discovered that the lipase catalysis can be attributed to basic amino acid residues as the catalysts to promote Michael addition, especially when tertiary amide solvents partially unfold the protein and expose its (basic) amino acid residues.

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 score0.024
Threshold uncertainty score0.180

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 head0.003
GPT teacher head0.210
Teacher spread0.207 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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