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Identification of acetylcholinesterase inhibitors from traditional medicinal plants for Alzheimer's disease using <i>in silico</i> and machine learning approaches

Md. Tarikul Islam, Md. Aktaruzzaman, Ahmed Saif, ATM Hasibul Hasan, Md. Mehedi Hasan Sourov, Bratati Sikdar, Saira Rehman, Afrida Tabassum, Syed Abeed-Ul-Haque, Mehedi Hasan Sakib, Md. Muntasir Alam Muhib, Md. Ali Ahasan Setu, Faria Tasnim, Rifat Rayhan, Mohamed M. Abdel‐Daim, Md. Obayed Raihan

2024RSC Advances30 citationsDOIOpen Access PDF

Abstract

values. Molecular docking studies of these 32 compounds revealed various binding energies with AChE, with the best three compounds (CID 102267534, CID 15161648, CID 12441) selected for further analysis. MM-GBSA studies confirmed the promising binding energies of these three compounds, validating the molecular docking study. Further, the MD simulation studies have confirmed the structural and conformational stability of these three protein-ligand complexes. Finally, DFT calculations revealed favorable chemical features of these compounds. Thus, we can conclude that these three compounds (CID 102267534, CID 15161648, CID 12441) may inhibit the activity of AChE and can be useful as a treatment for Alzheimer's disease.

Topics & Concepts

AcetylcholinesteraseIn silicoAchéAcetylcholineDiseaseAcetylcholinesterase inhibitorIdentification (biology)PharmacologyCognitive impairmentComputational biologyNeuroscienceMedicinePsychologyChemistryBiologyBiochemistryEnzymeInternal medicineBotanyGeneComputational Drug Discovery MethodsCholinesterase and Neurodegenerative DiseasesMedicinal Plants and Neuroprotection
Identification of acetylcholinesterase inhibitors from traditional medicinal plants for Alzheimer's disease using <i>in silico</i> and machine learning approaches | Litcius