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Record W4414770424 · doi:10.1016/j.carres.2025.109691

Deoxygenated analogs of 2-deoxy-2,3-didehydro-N-acetyl neuraminic acid as inhibitors of human neuraminidase enzymes

2025· article· en· W4414770424 on OpenAlexafffund
Nahoko Yagami, Fatma Eljabu, Manas Jana, Elisa Garcia Carvajal, Christopher W. Cairo

Bibliographic record

VenueCarbohydrate Research · 2025
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsUniversity of Alberta
FundersCanadian Glycomics NetworkNatural Sciences and Engineering Research Council of Canada
KeywordsNeuraminidaseNeuraminic acidEnzymePotencySialic acidSialidaseStructure–activity relationshipIsozymeIn vitro

Abstract

fetched live from OpenAlex

There is increasing interest in carbohydrate analogs for drug development, and the polar nature of these targets presents a challenge for medicinal chemistry. Multiple substrate hydroxy groups are typically required for enzyme active site recognition. Not all of these polar groups will have the same importance in recognition. A common strategy is to replace or remove these groups and compare the activity of the resulting analogs. If hydroxy groups are non-essential, or if their removal results in increased potency they may form the basis of improved inhibitors or substrates. In our studies of human neuraminidase enzymes (NEU), we have identified modifications at the C5 and C9 positions of the 2-deoxy-2,3-didehydro-N-acetyl neuraminic (DANA) scaffold that provide potent and selective inhibitors. In this study, we sought to test the requirements of each of the four human NEU isoenzymes for the presence of O4, O7, O8, or O9 hydroxy groups found in DANA. We synthesized the corresponding mono- (4, 7, 8, and 9) and di-deoxy (7,9; 7,8; and 8,9) analogs of DANA and tested their potency against human NEU. We found that 8-deoxy compounds increased potency against NEU2 and NEU3. Additionally, several di-deoxy analogs were tolerated by NEU1, NEU2, and NEU3. Finally, we generated known selective inhibitors of NEU3 and NEU4 and tested their 8-deoxy analogs. Combination of these features did not improve overall potency, suggesting deoxygenated analogs will require additional optimization.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.041
GPT teacher head0.362
Teacher spread0.321 · 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.

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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