Computational mechanistic insight of fungal metabolites for novel acetylcholinesterase inhibitors

Hadeel Alyenbaawi; Mohammed Alsaweed; Qazi Mohammad Sajid Jamal; Mohammad Rehan Asad; Syed Mohd Danish Rizvi; Fuzail Ahmad; Mehnaz Kamal; Danish Iqbal

doi:10.1007/s11030-025-11254-y

Computational mechanistic insight of fungal metabolites for novel acetylcholinesterase inhibitors

Mol Divers. 2025 Jun 21. doi: 10.1007/s11030-025-11254-y. Online ahead of print.

Authors

Hadeel Alyenbaawi^#¹, Mohammed Alsaweed², Qazi Mohammad Sajid Jamal³, Mohammad Rehan Asad⁴, Syed Mohd Danish Rizvi⁵, Fuzail Ahmad⁶, Mehnaz Kamal⁷, Danish Iqbal^#⁸

Affiliations

¹ Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, 11952, Majmaah, Saudi Arabia. hadeel.a@mu.edu.sa.
² Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, 11952, Majmaah, Saudi Arabia.
³ Department of Health Informatics, College of Applied Medical Sciences, Qassim University, P.O. Box 6666, 51452, Buraydah, Saudi Arabia.
⁴ Department of Basic Medical Science, College of Medicine, Majmaah University, 11952, Al Majmaah, Saudi Arabia.
⁵ Department of Pharmaceutics, College of Pharmacy, University of Hail, P.O. Box 2240, Hail, Saudi Arabia.
⁶ Respiratory Care Department, College of Applied Sciences, Almaarefa University, Diriya, 13713, Riyadh, Saudi Arabia.
⁷ Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, 11942, Al-Kharj, Saudi Arabia.
⁸ Department of Health Information Management, College of Applied Medical Sciences, Buraydah Private Colleges, 51418, Buraydah, Saudi Arabia. danishiqbalmail@gmail.com.

^# Contributed equally.

PMID: 40542966
DOI: 10.1007/s11030-025-11254-y

Abstract

Activity of acetylcholinesterase (AChE) enzyme elevation has been frequently observed in Alzheimer's disease (AD) and plays a key role in disease progression. Therefore, its inhibition is considered a crucial therapeutic step in the management of cognitive defects associated with AD. In this study, we screened a library of fungal metabolites using molecular docking, molecular dynamics, and PCA to identify metabolic compounds that effectively worked against AChE. An extensive database of 19,667 fungal metabolites was methodically filtered to identify compounds with drug-like properties that are suitable for neurological disorders. Of all metabolites, only four compounds inhibited AChE better than donepezil. Mangrovamide F was the most effective against AChE, followed by Libertellenone M, Tricholopardin A, and Aspeterreurone A (ΔG: -12.6 ± 0.2, -12.3 ± 0.2, -12.2 ± 0.2, -11.8 ± 0.1 kcal/mol, respectively). Aspeterreurone A had the highest LD₅₀ dose (39,800 mg/kg), followed by Tricholopardin A (8350 mg/kg), Mangrovamide F (707 mg/kg), and Libertellenone M (190 mg/kg). Over the course of the 200-ns simulation, the protein in the AChE-fungal metabolite complexes stabilized and fluctuated within the permissible range. The most important residue, TRP86, in the AChE protein often interacts with all the best-hit ligands primarily through hydrophobic interactions, for the longest period with Libertellenone M, followed by Tricholopardin A, Mangrovamide F, Donepezil, and Aspeterreurone A. According to our PCA data, Mangrovamide F (44.61%) had the highest eigenvalue rank, followed by Libertellenone M (27.49%), Aspeterreurone A (23%), and Tricholopardin A (20.02%). Mangrovamide F and Tricholopardin A were found to be the best inhibitors of AChE enzyme with acceptable LD₅₀ and have less toxicity. Further in vitro and in vivo works regarding the therapeutic effects of these fungal compounds could elaborate our findings.

Keywords: Acetylcholinesterase; Fungal metabolites; Molecular docking; Molecular dynamics simulation; Neurological disorders.

Abstract

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