In silico identification of novel stilbenes analogs for potential multi-targeted drugs against Alzheimer’s disease

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Context: Alzheimer’s disease (AD) is a chronic progressive neurodegenerative syndrome, which adversely disturbs cognitive abilities as well as intellectual processes and frequently occurs in the elderly. Inhibition of cholinesterase is a valuable approach to upsurge acetylcholine concentrations in the brain and persuades the development of multi-targeted ligands against cholinesterases. Methods: The current study aims to determine the binding potential accompanied by antioxidant and anti-inflammatory activities of stilbenes-designed analogs against both cholinesterases (Acetylcholinesterase and butyrylcholinesterase) and neurotrophin targets for effective AD therapeutics. Docking results have shown that the WS6 compound exhibited the least binding energy − 10.1 kcal/mol with Acetylcholinesterase and − 7.8 kcal/mol with butyrylcholinesterase. The WS6 also showed a better binding potential with neurotrophin targets that are Brain-derived Neurotrophic Factor, Neurotrophin 4, Nerve Growth Factor, and Neurotrophin 3. The tested compounds particularly WS6 revealed significant antioxidant and anti-inflammatory activities through the comparative docking analysis with Fluorouracil and Melatonin as control drugs of antioxidants while Celecoxib and Anakinra as anti-inflammatory. The bioinformatics approaches including molecular docking calculations followed by the pharmacokinetics analysis and molecular dynamic simulations were accomplished to explore the capabilities of designed stilbenes as effective and potential leads. Root mean square deviation, root mean square fluctuations, and MM-GBSA calculations were performed through molecular dynamic simulations to extract the structural and residual variations and binding free energies through the 50-ns time scale.




Firdoos, S., Dai, R., Tahir, R. A., Khan, Z. Y., Li, H., Zhang, J., … Qing, H. (2023). In silico identification of novel stilbenes analogs for potential multi-targeted drugs against Alzheimer’s disease. Journal of Molecular Modeling, 29(7).

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