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Record W1948767545 · doi:10.5539/jas.v7n9p26

Screening Flavonoids for Inhibition of Acetylcholinesterase Identified Baicalein as the Most Potent Inhibitor

2015· article· en· W1948767545 on OpenAlexvenueno aff
Azize Balkis, Khoa Tran, Yan Zhi Lee, Ken Ng

Bibliographic record

VenueJournal of Agricultural Science · 2015
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsBaicaleinChemistryDissociation constantStereochemistryAcetylcholinesteraseEnzymeEnzyme inhibitorIC50Scutellaria baicalensisInhibitory postsynaptic potentialMixed inhibitionNon-competitive inhibitionBiochemistryIn vitroPharmacology

Abstract

fetched live from OpenAlex

Screening phenolic and polyphenolic compounds for inhibitory activity against electric eels acetylcholinesterase (AChE) identified baicalein, a major flavone derived from the roots of Scutellaria baicalensis, as the most potent inhibitor with IC50 (concentration required for 50% inhibition) of 0.61 µM. None of the hydroxybenzoic and hydroxycinnamic acids screened showed inhibitory activity measured at 100 µM. Structure-activity relationships based on IC50 values of the active flavonoids showed that inhibitory activity (a) required the unsaturated 2-phenyl-chroman structure, (b) has strong requirement for the A-ring A5-OH, A6-OH and A7-OH groups (b) does not depend on B-ring hydroxyl groups, and (d) was reduced by bulky sugar substitution of the saturated C-ring C3-OH. Enzyme kinetic analysis showed that baicalein is a mixed inhibitor of AChE with K1 (equilibrium constant of dissociation of the inhibitor bound enzyme complex) and K2 (equilibrium constant of dissociation of the inhibitor bound enzyme-substrate complex) of 0.91 and 1.98 µM, respectively.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.315
Teacher spread0.272 · 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

Citations77
Published2015
Admission routes1
Has abstractyes

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