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Record W2913170358 · doi:10.1038/s12276-019-0205-7

Inhibition of β-site amyloid precursor protein cleaving enzyme 1 and cholinesterases by pterosins via a specific structure−activity relationship with a strong BBB permeability

2019· article· en· W2913170358 on OpenAlexaff
Susoma Jannat, Anand Balupuri, Md Yousof Ali, Seong Su Hong, Chun Whan Choi, Yun-Hyeok Choi, Jin‐Mo Ku, Woo Jung Kim, Jae Yoon Leem, Ju Eun Kim, Abinash Chandra Shrestha, Ha Neul Ham, Kee-Ho Lee, Dong‐Min Kim, Nam Sook Kang, Gil Hong Park

Bibliographic record

VenueExperimental & Molecular Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsConcordia University
FundersKorea UniversityKorea University Medicine
KeywordsButyrylcholinesteraseAcetylcholinesteraseEnzymeChemistryIC50BiochemistryBinding siteAchéStereochemistryIn vitro

Abstract

fetched live from OpenAlex

We extracted 15 pterosin derivatives from Pteridium aquilinum that inhibited β-site amyloid precursor protein cleaving enzyme 1 (BACE1) and cholinesterases involved in the pathogenesis of Alzheimer’s disease (AD). (2R)-Pterosin B inhibited BACE1, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) with an IC50 of 29.6, 16.2 and 48.1 µM, respectively. The Ki values and binding energies (kcal/mol) between pterosins and BACE1, AChE, and BChE corresponded to the respective IC50 values. (2R)-Pterosin B was a noncompetitive inhibitor against human BACE1 and BChE as well as a mixed-type inhibitor against AChE, binding to the active sites of the corresponding enzymes. Molecular docking simulation of mixed-type and noncompetitive inhibitors for BACE1, AChE, and BChE indicated novel binding site-directed inhibition of the enzymes by pterosins and the structure−activity relationship. (2R)-Pterosin B exhibited a strong BBB permeability with an effective permeability (Pe) of 60.3×10−6 cm/s on PAMPA-BBB. (2R)-Pterosin B and (2R,3 R)-pteroside C significantly decreased the secretion of Aβ peptides from neuroblastoma cells that overexpressed human β-amyloid precursor protein at 500 μM. Conclusively, our study suggested that several pterosins are potential scaffolds for multitarget-directed ligands (MTDLs) for AD therapeutics. Compounds extracted from bracken fern block the activity of three enzymes associated with Alzheimer’s disease (AD). Because AD is a complex and multifactorial disease, a multitarget-directed approach is an attractive strategy for the development of disease-modifying therapeutics. A study led by Gil Hong Park, Korea University, Seoul, and Nam Sook Kang, Chungnam National University, Daejon, revealed that pterosin derivatives could reduce the activity of β-site amyloid precursor protein cleaving enzyme 1, acetylcholinesterase and butyrylcholinesterase in a concentration-dependent manner. Furthermore, the fern-extracted compounds did not cause cellular toxicity and were able to cross the blood–brain barrier, which is impermeable to most drugs, to reach the brain. Future studies will determine whether they can be developed into drugs to simultaneously engage various AD targets in animal models of the disease.

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 score0.000
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)0.0000.000

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 head0.014
GPT teacher head0.277
Teacher spread0.262 · 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

Citations45
Published2019
Admission routes1
Has abstractyes

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