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• W3148392921 endingPage "1996" @default.
• W3148392921 startingPage "1996" @default.
• W3148392921 abstract "Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same." @default.
• W3148392921 created "2021-04-13" @default.
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• W3148392921 date "2021-04-01" @default.
• W3148392921 modified "2023-10-16" @default.
• W3148392921 title "Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docking Approaches" @default.
• W3148392921 cites W1586801841 @default.
• W3148392921 cites W1602284078 @default.
• W3148392921 cites W1965607248 @default.
• W3148392921 cites W1971849220 @default.
• W3148392921 cites W1974900617 @default.
• W3148392921 cites W1981506665 @default.
• W3148392921 cites W1999491936 @default.
• W3148392921 cites W1999985301 @default.
• W3148392921 cites W2003752196 @default.
• W3148392921 cites W2003873735 @default.
• W3148392921 cites W2011854099 @default.
• W3148392921 cites W2012411261 @default.
• W3148392921 cites W2020112979 @default.
• W3148392921 cites W2023251219 @default.
• W3148392921 cites W2039478311 @default.
• W3148392921 cites W2043996867 @default.
• W3148392921 cites W2046506973 @default.
• W3148392921 cites W2046817513 @default.
• W3148392921 cites W2049466195 @default.
• W3148392921 cites W2054126920 @default.
• W3148392921 cites W2066918975 @default.
• W3148392921 cites W2073543631 @default.
• W3148392921 cites W2080703820 @default.
• W3148392921 cites W2084057506 @default.
• W3148392921 cites W2085801244 @default.
• W3148392921 cites W2085907924 @default.
• W3148392921 cites W2086729168 @default.
• W3148392921 cites W2087661061 @default.
• W3148392921 cites W2087845345 @default.
• W3148392921 cites W2108791885 @default.
• W3148392921 cites W2136198395 @default.
• W3148392921 cites W2136249409 @default.
• W3148392921 cites W2145962544 @default.
• W3148392921 cites W2152850192 @default.
• W3148392921 cites W2158735110 @default.
• W3148392921 cites W2160592148 @default.
• W3148392921 cites W2167526480 @default.
• W3148392921 cites W2173733507 @default.
• W3148392921 cites W2265237353 @default.
• W3148392921 cites W2293921324 @default.
• W3148392921 cites W2299014331 @default.
• W3148392921 cites W2500149077 @default.
• W3148392921 cites W2552021415 @default.
• W3148392921 cites W2586919770 @default.
• W3148392921 cites W2595817212 @default.
• W3148392921 cites W2611425558 @default.
• W3148392921 cites W2616820723 @default.
• W3148392921 cites W2756083956 @default.
• W3148392921 cites W2767476432 @default.
• W3148392921 cites W2768472689 @default.
• W3148392921 cites W2786517090 @default.
• W3148392921 cites W2790505242 @default.
• W3148392921 cites W2799453939 @default.
• W3148392921 cites W2802505016 @default.
• W3148392921 cites W2803774088 @default.
• W3148392921 cites W2808304326 @default.
• W3148392921 cites W2914877425 @default.
• W3148392921 cites W2966471646 @default.
• W3148392921 cites W2978873019 @default.
• W3148392921 cites W2994629524 @default.
• W3148392921 cites W2999197824 @default.
• W3148392921 cites W3024269707 @default.
• W3148392921 cites W3024545198 @default.
• W3148392921 cites W3085034201 @default.
• W3148392921 cites W4211135065 @default.
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• W3148392921 doi "https://doi.org/10.3390/molecules26071996" @default.
• W3148392921 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8037217" @default.
• W3148392921 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33915968" @default.
• W3148392921 hasPublicationYear "2021" @default.
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