MétaCan
Menu
Back to cohort
Record W2314949866 · doi:10.1021/bi201019n

Bacterial and Viral Sialidases: Contribution of the Conserved Active Site Glutamate to Catalysis

2011· article· en· W2314949866 on OpenAlexaff
Jefferson Chan, Jacqueline N. Watson, April Lu, Viviana C. Cerda, Thor J. Borgford, Andrew J. Bennet

Bibliographic record

VenueBiochemistry · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEnzyme kineticsSialidaseChemistryResidue (chemistry)BiochemistryActive siteStereochemistryMutantEnzymeNeuraminidase

Abstract

fetched live from OpenAlex

Mutagenesis of the conserved glutamic acid of influenza type A (E277) and Micromonospora viridifaciens (E260) sialidases was performed to probe the contribution of this strictly conserved residue to catalysis. Kinetic studies of the E260D and E260C M. viridifaciens mutant enzymes reveal that the overall mechanism of action has not changed. That is, the mutants are retaining sialidases in which glycosylation and deglycosylation are rate-limiting for k(cat)/K(m) and k(cat), respectively. The solvent kinetic isotope effect and proton inventory on k(cat) for the E260C mutant sialidase provide strong evidence that the newly installed cysteine residue provides little catalytic acceleration. The results are consistent with the conserved aspartic acid residue (D92) becoming the key general acid/base residue in the catalytic cycle. In addition, the E277D mutant influenza type A sialidase is catalytically active toward 4-nitrophenyl α-D-sialoside, although no measurable hydrolysis of natural substrates was observed. Thus, mutating the glutamate residue (E277) to an aspartate increases the activation free energy of hydrolysis for natural substrates by >22 kJ/mol.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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

Citations15
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueBiochemistrySame topicGlycosylation and Glycoproteins ResearchFrench-language works237,207