Abstract

Alzheimer’s disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50 values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models afforded R2, n}{}{Q}_{mathrm{CV }}^{2} and n}{}{Q}_{mathrm{Ext}}^{2} values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it afforded R2, n}{}{Q}_{mathrm{CV }}^{2} and n}{}{Q}_{mathrm{Ext}}^{2} values of 0.92 ± 0.01, 0.78 ± 0.06 and 0.78 ± 0.05, respectively. Furthermore, Y-scrambling was applied to evaluate the possibility of chance correlation of the predictive model. Subsequently, a thorough analysis of the substructure fingerprint count was conducted to provide informative insights on the inhibitory activity of AChE inhibitors. Moreover, Kennard–Stone sampling of the actives were applied to select 30 diverse compounds for further molecular docking studies in order to gain structural insights on the origin of AChE inhibition. Site-moiety mapping of compounds from the diversity set revealed three binding anchors encompassing both hydrogen bonding and van der Waals interaction. Molecular docking revealed that compounds 13, 5 and 28 exhibited the lowest binding energies of −12.2, −12.0 and −12.0 kcal/mol, respectively, against human AChE, which is modulated by hydrogen bonding, π–π stacking and hydrophobic interaction inside the binding pocket. These information may be used as guidelines for the design of novel and robust AChE inhibitors.

Highlights

  • Neurodegenerative diseases is caused by the progressive loss of neural cells thereby leading to nervous system dysfunction (Beal, 1995; Kuca et al, 2016)

  • molecular weight (MW) represents the molecular size of a compound that is commonly used because of it can be interpreted and calculated as well as appropriate size of a compound is important for its passage via lipid membrane

  • ALogP is a widely used parameter for determining the lipophilicity of a compound and used in calculating the membrane penetration and permeability of compounds. nHBDon and number of hydrogen bond acceptor (nHBAcc) describe the number of hydrogen bond donors and hydrogen bond acceptors, respectively, which is used to measuring hydrogen bonding capacity

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Summary

Introduction

Neurodegenerative diseases is caused by the progressive loss of neural cells thereby leading to nervous system dysfunction (Beal, 1995; Kuca et al, 2016). Alzheimer’s disease (AD) is a debilitating illness that is expected to triple by the year 2050 (Brookmeyer et al, 2007). The pathological changes in AD are mainly attributed to the dramatic loss of neurons in many areas of the central nervous system accompanied by a great reduction in the levels of neurotransmitters. Acetylcholine (ACh) is a neurotransmitter possessing important cognitive and muscular functions. In the peripheral nervous system, ACh is found at the neuromuscular junction where it is involved in muscle contraction while in the central nervous system, it is involved in cognitive functions such as thought, learning and memory

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