In silico screening of naturally derived dietary compounds as potential butyrylcholinesterase inhibitors for Alzheimer’s disease treatment
Alzheimer's disease (AD) is a progressive neurodegenerative condition that causes a substantial decline in cognitive functions and affects memory, thinking abilities, and daily behavior. The most prominent hallmark of AD pathogenesis is the formation of amyloid-β plaques, among other associated pathways such as neurofibrillary tangles, mitochondrial dysfunction, neuroinflammation, and oxidative stress. Butyrylcholinesterase (BuChE), an acetylcholine-degrading enzyme, plays a critical role in the progression of Alzheimer's disease, particularly through its involvement in amyloid-β plaque formation. Thus, the inhibition of BuChE is considered a valuable therapeutic strategy for the management of AD. The present study aimed to identify potential bioactive chemicals from naturally occurring dietary compounds that could improve neurocognitive function and appear as a viable treatment for AD by inhibiting the function of BuChE. A small library of 44 natural dietary chemicals from a variety of dietary plants was subjected to comprehensive in silico studies, including molecular docking, molecular mechanics generalized born surface area (MM-GBSA) calculations, pharmacokinetics assessments, toxicity profiles, molecular dynamics (MD) simulation, and density functional theory (DFT) analysis. These studies revealed that CID 129886986 and CID 115269 showed stronger binding affinities with drug-likeness and no toxicity than the FDA-approved standard drug, Donepezil. Additionally, they exhibited strong structural stability with fewer fluctuations throughout the simulation, making them promising candidates for Alzheimer's disease treatment.
Authors
- Amany Ahmed Sayed (ORCID: https://orcid.org/0000-0001-7385-3686)
- Ghadeer Mohsen Albadrani (ORCID: https://orcid.org/0000-0001-5657-4650)
- Mohamed M. Abdel‐Daim (ORCID: https://orcid.org/0000-0002-4341-2713)
- Md. Obayed Raihan (ORCID: https://orcid.org/0000-0002-0095-5339)
- Kishore Kumar Sarkar (ORCID: https://orcid.org/0000-0001-6127-6412)
- Muath Q. Al‐Ghadi (ORCID: https://orcid.org/0000-0002-0093-321X)
- Md. Aktaruzzaman (ORCID: https://orcid.org/0000-0003-1570-3588)
- ATM Hasibul Hasan (ORCID: https://orcid.org/0009-0000-2810-8660)
- Md. Tarikul Islam (ORCID: https://orcid.org/0000-0002-3266-4229)
- Chandan Barai
- Humayra Afroz Dona
- Farhan Ishrak Rafi
- Tasfiah Tasnim
- Parvej Sarder
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Suez Canal University (EG)
- Cairo University (EG)
- King Saud University (SA)
- Jagannath University (BD)
- Computational Physics (United States) (US)
- Batterjee Medical College
- BRAC University (BD)
- University of Rajshahi (BD)
Publication Details
- Journal
- Scientific Reports
- Published
- 2025-05-17
- DOI
- https://doi.org/10.1038/s41598-025-98092-y
- Citations
- 6
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 9.03
Funders
- King Saud University
- Princess Nourah Bint Abdulrahman University