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Record W7117483210 · doi:10.1039/d5ob01796c

Determinants of undesired α2-6-sialoside formation by PmST1 M144D

2025· article· en· W7117483210 on OpenAlexafffund
Fahima Mozaneh, Peng Wu

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsUniversity of Alberta
FundersCanadian Glycomics NetworkNational Institutes of HealthNational Institute of General Medical SciencesCanada Research Chairs
KeywordsAglyconeGlycosidic bondSulfationGlycanEnzymeSialic acidRegioselectivity

Abstract

fetched live from OpenAlex

α2-3-sialyltransferase 1 (PmST1) is a widely used enzyme in chemoenzymatic synthesis. In particular, the PmST1 M144D mutant is routinely employed as an α2-3-sialyltransferase, although only low levels of α2-6-sialyltransferase activity have been reported. Here, we discover that for certain acceptors, the formation of the undesired α2-6-sialoside can reach up to 20% of the product. To elucidate the factors that influence this regioselectivity, we systematically examined the effects of (i) sulfation of the acceptor, (ii) the chemical nature of the aglycone, (iii) pH, and (iv) the extent of reaction completion. The results indicate that sulfation at the 6-position of GlcNAc or a β-ethyl-NHCbz aglycone is a factor that can increase the amount of α2-6 sialoside product. Surprisingly, pH had only a small impact, and the amount of α2-6 sialoside product did not differ over the course of the reaction. These findings provide insights into the enzymatic specificity of PmST1 M144D and inform its optimized use in chemo-enzymatic synthesis of defined sialosides.

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)0.001
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: 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
Metaresearch0.0000.001
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)0.0010.000

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 head0.006
GPT teacher head0.264
Teacher spread0.258 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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