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Updated: Oct 18, 2025

Quantitative 3D In Silico Modeling q3DISM of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease
Published on: December 26, 2016
Identification of novel acetylcholinesterase inhibitors through 3D-QSAR, molecular docking, and molecular dynamics
Khalil El Khatabi1, Reda El-Mernissi2, Ilham Aanouz2
1Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco. khalil.elkhatabi@edu.umi.ac.ma.
Abstract:
Acetylcholinesterase (AChE) is a potential target for the development of small molecules as inhibitors for the therapy of Alzheimer's disease (AD). To design highly active acetylcholinesterase inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) approach was performed on a series of N-benzylpyrrolidine derivatives previously evaluated for acetylcholinesterase inhibitory activity. The developed two models, CoMFA and CoMSIA, were statistically validated, and good predictability was achieved for both models. The information generated from 3D-QSAR contour maps may provide a better understanding of the structural features required for acetylcholinesterase inhibition and help to design new potential anti-acetylcholinesterase molecules. Consequently, six novel acetylcholinesterase inhibitors were designed, among which compound A1 with the highest predicted activity was subjected to detailed molecular docking and compared to the most active compound. Extra-precision molecular dynamics (MD) simulation of 50 ns and binding free energy calculations using MM-GBSA were performed for the selected compounds to validate the stability. These results may afford important structural insights needed to identify novel acetylcholinesterase inhibitors and other promising strategies in drug discovery.
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