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Record W2051271940 · doi:10.1139/v07-011

Acyl transfer from carboxylate, carbonate, and thiocarbonate esters to enzymatic and nonenzymatic thiolates

2007· article· en· W2051271940 on OpenAlexfundvenueno aff
Christian Gravel, Danielle Lapierre, Judith Labelle, Jeffrey W. Keillor

Bibliographic record

VenueCanadian Journal of Chemistry · 2007
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryAcylationCarboxylateThioesterStereochemistryLysineElectrophileCysteineReactivity (psychology)Organic chemistryEnzymeCombinatorial chemistryAmino acidBiochemistryCatalysis

Abstract

fetched live from OpenAlex

Transglutaminases (EC 2.3.2.13) (TGases) catalyze calcium-dependent acyl transfer reactions between peptide-bound glutamine residues as acyl donors and peptide-bound lysine residues as acyl acceptors, resulting in the formation of intermolecular ε-(γ-glutamyl)lysine crosslinks. The mechanistic details of its "ping-pong" transamidation reaction remain unknown. In particular, few studies have been published probing the nucleophilicity of TGase using acyl-donor substrates of varied electrophilicity. Herein we report the synthesis of activated esters of carbonates, carbamates, and thiocarbonates and their reactions with simple thiols, as a nonenzymatic point of reference, and with the catalytic cysteine residue of guinea pig liver TGase. Our kinetic results show that the simple substitution of a side chain methylene unit by oxygen or sulphur had a surprising effect on both substrate affinity and acylation reactivity. Furthermore, they provide unexpected insight into the importance of a side chain heteroatom for conferring affinity for tissue TGase as well as revealing an interesting class of irreversible inhibitors.Key words: enzyme kinetics, enzyme inhibition, transglutaminase, acyl-transfer reactions, carbamate, thiocarbonate, carbonate.

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 score0.232
Threshold uncertainty score0.485

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 head0.202
Teacher spread0.194 · 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

Citations12
Published2007
Admission routes2
Has abstractyes

Explore more

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