Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: anin silicoapproach

Pravin Ambure , Jyotsna Bhat , Tomasz Puzyn , Kunal Roy


Alzheimer’s disease (AD) is a multi-factorial disease, which can be simply outlined as an irreversible and progressive neurodegenerative disorder with an unclear root cause. It is a major cause of dementia in old aged people. In the present study, utilizing the structural and biological activity information of ligands for five important and mostly studied vital targets (i.e. cyclin-dependant kinase 5, β-secretase, monoamine oxidase B, glycogen synthase kinase 3β, acetylcholinesterase) that are believed to be effective against AD, we have developed five classification models using linear discriminant analysis (LDA) technique. Considering the importance of data curation, we have given more attention towards the chemical and biological data curation, which is a difficult task especially in case of big data-sets. Thus, to ease the curation process we have designed Konstanz Information Miner (KNIME) workflows, which are made available at The developed models were appropriately validated based on the predictions for experiment derived data from test sets, as well as true external set compounds including known multi-target compounds. The domain of applicability for each classification model was checked based on a confidence estimation approach. Further, these validated models were employed for screening of natural compounds collected from the InterBioScreen natural database ( Further, the natural compounds that were categorized as ‘actives’ in at least two classification models out of five developed models were considered as multi-target leads, and these compounds were further screened using the drug-like filter, molecular docking technique and then thoroughly analyzed using molecular dynamics studies. Finally, the most potential multi-target natural compounds against AD are suggested.
Author Pravin Ambure
Pravin Ambure,,
, Jyotsna Bhat (FCh / DEChR / LECh)
Jyotsna Bhat,,
- Laboratory of Environmental Chemometrics
, Tomasz Puzyn (FCh / DEChR / LECh)
Tomasz Puzyn,,
- Laboratory of Environmental Chemometrics
, Kunal Roy
Kunal Roy,,
Journal seriesJournal of Biomolecular Structure & Dynamics, ISSN 0739-1102, (N/A 70 pkt)
Issue year2019
Publication size in sheets1.2
Keywords in EnglishAlzheimer’s disease, multi-target drug design, natural compounds, data curation, big data, linear discriminant analysis, molecular docking, molecular dynamics
ASJC Classification1312 Molecular Biology; 2700 General Medicine; 1315 Structural Biology
Languageen angielski
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 17-11-2019, ArticleFromJournal
Publication indicators WoS Citations = 4; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.787; WoS Impact Factor: 2018 = 3.31 (2) - 2018=2.689 (5)
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