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Record W2798262172 · doi:10.1021/acs.biochem.8b00117

Both Chemical and Non-Chemical Steps Limit the Catalytic Efficiency of Family 4 Glycoside Hydrolases

2018· article· en· W2798262172 on OpenAlexafffund
Natalia Sannikova, Chloe A. N. Gerak, Fahimeh S. Shidmoossavee, Dustin T. King, Saeideh Shamsi Kazem Abadi, Andrew R. Lewis, Andrew J. Bennet

Bibliographic record

VenueBiochemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlycoside hydrolaseGlycosideCatalysisChemistryLimit (mathematics)Organic chemistryBiochemistryEnzymeMathematics

Abstract

fetched live from OpenAlex

The glycoside hydrolase family 4 (GH4) α-galactosidase from Citrobacter freundii (MelA) catalyzes the hydrolysis of fluoro-substituted phenyl α-d-galactopyranosides by utilizing two cofactors, NAD+ and a metal cation, under reducing conditions. In order to refine the mechanistic understanding of this GH4 enzyme, leaving group effects were measured with various metal cations. The derived βlg value on V/K for strontium activation is indistinguishable from zero (0.05 ± 0.12). Deuterium kinetic isotope effects (KIEs) were measured for the activated substrates 2-fluorophenyl and 4-fluorophenyl α-d-galactopyranosides in the presence of Sr2+, Y3+, and Mn2+, where the isotopic substitution was on the carbohydrate at C-2 and/or C-3. To determine the contributing factors to the virtual transition state (TS) on which the KIEs report, kinetic isotope effects on isotope effects were measured on these KIEs using doubly deuterated substrates. The measured DV/K KIEs for MelA-catalyzed hydrolysis of 2-fluorophenyl α-d-galactopyranoside are closer to unity than the measured effects on 4-fluorophenyl α-d-galactopyranoside, irrespective of the site of isotopic substitution and of the metal cation activator. These observations are consistent with hydride transfer at C-3 to the on-board NAD+, deprotonation at C-2, and a non-chemical step contributing to the virtual TS for V/K.

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 score0.001
Threshold uncertainty score0.463

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 head0.228
Teacher spread0.220 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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