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Record W2325242985 · doi:10.1021/jo401854w

Exploitation of the Catalytic Site and 150 Cavity for Design of Influenza A Neuraminidase Inhibitors

2013· article· en· W2325242985 on OpenAlexafffund
Pal John Pal Adabala, Eric B. LeGresley, Nicole Bance, Masahiro Niikura, Bernardine M. Pinto

Bibliographic record

VenueThe Journal of Organic Chemistry · 2013
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeuraminidaseActive siteEnzymeChemistryAzideStereochemistryIn vitroAllylic rearrangementStrain (injury)Influenza A virusVirusIC50Lead compoundCatalysisCombinatorial chemistryBiochemistryVirologyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

We report here the exploitation of the 150 cavity in the active site of influenza A viral neuraminidases for the design of novel C-6 triazole-containing Tamiflu derivatives. A general and convenient synthetic route was developed by utilizing a highly substituted cyclic Baylis-Hillman acetate as an active precursor for azide substitution via suprafacial allylic azide [3,3]-sigmatropic rearrangement. Virus replication inhibitory assays in vitro of these triazole derivatives containing either an amino or guanidino function indicated that the guanidinium compound showed the higher efficacy against a strain with N2 subtype at a concentration of 2 × 10(-5) M but did not inhibit replication of a strain with N1 subtype even at a concentration of 10(-4) M. In order to probe the nature of the enzyme-inhibitor interactions, molecular dynamics simulations were performed on complexes of these compounds with different neuraminidase enzymes. The results indicated that the candidate inhibitors occupy both the 150 cavity and catalytic site but with alternating occupancy.

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 score0.002

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)0.0010.000

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 head0.055
GPT teacher head0.319
Teacher spread0.264 · 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

Citations30
Published2013
Admission routes2
Has abstractyes

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