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Record W2014873582 · doi:10.1071/ch09059

Recent Developments in Glycoside Synthesis with Glycosynthases and Thioglycoligases

2009· article· en· W2014873582 on OpenAlexafffund
Bojana Rakić, Stephen G. Withers

Bibliographic record

VenueAustralian Journal of Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsBC Research (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlycoside hydrolaseChemistryGlycoconjugateGlycosideBiocatalysisGlycosylGlycolipidGlycosyl donorDirected evolutionGlycosyltransferaseCombinatorial chemistryEnzymeStereochemistryMutantBiochemistryCatalysisIonic liquid

Abstract

fetched live from OpenAlex

Glycosynthases are hydrolytically incompetent engineered glycosidases that catalyze the high-yielding synthesis of glycoconjugates from glycosyl fluoride donor substrates and appropriate acceptors. Glycosynthases from more than 10 glycoside hydrolase families have now been generated, allowing the synthesis of a wide range of oligosaccharides. Recent examples include glycosynthase-mediated syntheses of xylo-oligosaccharides, xyloglucans, glycolipids, and aryl glycosides. Glycosynthases have also now been generated from inverting glycosidases, increasing the range of enzyme scaffolds. Improvement of glycosynthase activity and broadening of specificity has been achieved through directed evolution approaches, and several novel high-throughput screens have been developed to allow this. Finally, metabolically stable glycoside analogues have been generated using another class of mutant glycosidases: thioglycoligases. Recent developments in all these aspects are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations27
Published2009
Admission routes2
Has abstractyes

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