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Record W2073517330 · doi:10.1155/2014/931756

Clicked Cinnamic/Caffeic Esters and Amides as Radical Scavengers and 5-Lipoxygenase Inhibitors

2014· article· en· W2073517330 on OpenAlexafffund
Jérémie A. Doiron, Benoît Métayer, Ryan Richard, Dany Desjardins, Luc H. Boudreau, Natalie A. Levesque, Jacques Jean‐François, Samuel Poirier, Marc E. Surette, Mohamed Touaibia

Bibliographic record

VenueInternational Journal of Medicinal Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversité LavalUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsNew Brunswick Innovation FoundationCanada Foundation for InnovationFondation de la recherche en santé du Nouveau-BrunswickUniversité de Moncton
KeywordsZileutonChemistryCaffeic acidCinnamic acidArachidonate 5-lipoxygenaseLipoxygenaseStereochemistryCycloadditionEnzymeBiochemistryArachidonic acidAntioxidantCatalysis

Abstract

fetched live from OpenAlex

5-Lipoxygenase (5-LO) is the key enzyme responsible for the conversion of arachidonic acid to leukotrienes, a class of lipid mediators implicated in inflammatory disorders. In this paper, we describe the design, synthesis, and preliminary activity studies of novel clicked caffeic esters and amides as radical scavengers and 5-LO inhibitors. From known 5-LO inhibitor 3 as a lead, cinnamic esters 8a-h and amides 9a-h as well as caffeic esters 15a-h and amides 16a-h were synthesized by Cu(I)-catalyzed [1,3]-dipolar cycloaddition with the appropriate azide precursors and terminal alkynes. All caffeic analogs are proved to be good radical scavengers (IC50: 10-20 μM). Esters 15g and 15f possessed excellent 5-LO inhibition activity in HEK293 cells and were equipotent with the known 5-LO inhibitor CAPE and more potent than Zileuton. Several synthesized esters possess activities rivaling Zileuton in stimulated human polymorphonuclear leukocytes.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.034
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.006
GPT teacher head0.257
Teacher spread0.251 · 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.

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

Citations6
Published2014
Admission routes2
Has abstractyes

Explore more

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