Issue 14, 2023

Exploiting butyrylcholinesterase inhibitors through a combined 3-D pharmacophore modeling, QSAR, molecular docking, and molecular dynamics investigation

Abstract

Alzheimer's disease (AD), a neurodegenerative condition associated with ageing, can occur. AD gradually impairs memory and cognitive function, which leads to abnormal behavior, incapacity, and reliance. By 2050, there will likely be 100 million cases of AD in the world's population. Acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibition are significant components of AD treatment. This work developed models using the genetic method multiple linear regression, atom-based, field-based, and 3-D pharmacophore modelling. Due to internal and external validation, all of the models have solid statistical (R2 > 0.81 and Q2 > 0.77) underpinnings. From a pre-plated CNS library (6055), we discovered a hit compound using virtual screening on a QSAR model. Through molecular docking, additional hit compounds were investigated (XP mode). Finally, a molecular dynamics simulation revealed that the Molecule5093-4BDS complex was stable (100 ns). Finally, the expected ADME properties for the hit compounds (Molecule5093, Molecule1076, Molecule4412, Molecule1053, and Molecule3344) were found. According to the results of our investigation and the prospective hit compounds, BuChE inhibitors may be used as a treatment for AD.

Graphical abstract: Exploiting butyrylcholinesterase inhibitors through a combined 3-D pharmacophore modeling, QSAR, molecular docking, and molecular dynamics investigation

Associated articles

Supplementary files

Article information

Article type
Paper
Submitted
25 Jan 2023
Accepted
14 Mar 2023
First published
23 Mar 2023
This article is Open Access
Creative Commons BY license

RSC Adv., 2023,13, 9513-9529

Exploiting butyrylcholinesterase inhibitors through a combined 3-D pharmacophore modeling, QSAR, molecular docking, and molecular dynamics investigation

S. Kumar, A. Manoharan, J. J, M. A. Abdelgawad, W. A. Mahdi, S. Alshehri, M. M. Ghoneim, L. K. Pappachen, S. M. Zachariah, T. P. Aneesh and B. Mathew, RSC Adv., 2023, 13, 9513 DOI: 10.1039/D3RA00526G

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