Hadeel Alyenbaawi, Mohammed Alsaweed, Qazi Mohammad Sajid Jamal, Mohammad Rehan Asad, Syed Mohd Danish Rizvi, Fuzail Ahmad, Mehnaz Kamal, Danish Iqbal
{"title":"Computational mechanistic insight of fungal metabolites for novel acetylcholinesterase inhibitors.","authors":"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","DOIUrl":null,"url":null,"abstract":"<p><p>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 LD<sub>50</sub> 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 LD<sub>50</sub> and have less toxicity. Further in vitro and in vivo works regarding the therapeutic effects of these fungal compounds could elaborate our findings.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Diversity","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s11030-025-11254-y","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including:
combinatorial chemistry and parallel synthesis;
small molecule libraries;
microwave synthesis;
flow synthesis;
fluorous synthesis;
diversity oriented synthesis (DOS);
nanoreactors;
click chemistry;
multiplex technologies;
fragment- and ligand-based design;
structure/function/SAR;
computational chemistry and molecular design;
chemoinformatics;
screening techniques and screening interfaces;
analytical and purification methods;
robotics, automation and miniaturization;
targeted libraries;
display libraries;
peptides and peptoids;
proteins;
oligonucleotides;
carbohydrates;
natural diversity;
new methods of library formulation and deconvolution;
directed evolution, origin of life and recombination;
search techniques, landscapes, random chemistry and more;