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

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Abstract

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.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on request.

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Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 92049102, 32070954, 82001167, 81870844). We thank the Biological and Medical Engineering Core Facilities of the Beijing Institute of Technology for their support.

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Authors and Affiliations

  1. Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China

    Sundas Firdoos, Rana Adnan Tahir, Hui Li, Jun Zhang, Junjun Ni, Zhenzhen Quan & Hong Qing

  2. Beijing Key Laboratory for Separation and Analysis in Biomedicine and Pharmaceutical, Beijing Institute of Technology (BIT), Beijing, 100081, People’s Republic of China

    Sundas Firdoos & Rongji Dai

  3. Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Muzaffarabad, Pakistan

    Rana Adnan Tahir

  4. Department of Computer Science and IT, University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan

    Zahid Younas Khan

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  1. Sundas Firdoos
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  9. Hong Qing
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Contributions

Contributions based on CRediT taxonomy: Sundas Firdoos: conceptualization, writing — original draft, writing — review and editing, methodology, investigation; Rongji Dai: supervision, writing — review and editing, methodology, investigation; Rana Adnan Tahir: methodology, writing — review and editing, investigation; Zahid Younas Khan: methodology, writing — review and editing; Hui Li, Jun Zhang and Junjun Ni: writing — review and editing; Zhenzhen Quan: methodology, investigation, resources, writing — review and editing; Hong Qing: methodology, investigation, writing — review and editing, funding acquisition, supervision.

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Correspondence to Sundas Firdoos or Rongji Dai.

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Firdoos, S., Dai, R., Tahir, R.A. et al. In silico identification of novel stilbenes analogs for potential multi-targeted drugs against Alzheimer’s disease. J Mol Model 29, 209 (2023). https://doi.org/10.1007/s00894-023-05609-1

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