Affiliation:
1. Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India
2. Department of Chemical Technology, University of Calcutta, 92 APC Road, Kolkata 700 032, India
Abstract
Background:
Alzheimer’s disease (AD), a neurological disorder, is the most common cause
of senile dementia. Butyrylcholinesterase (BuChE) enzyme plays a vital role in regulating the brain acetylcholine
(ACh) neurotransmitter, but in the case of Alzheimer’s disease (AD), BuChE activity gradually
increases in patients with a decrease in the acetylcholine (ACh) concentration via hydrolysis. ACh
plays an essential role in regulating learning and memory as the cortex originates from the basal forebrain,
and thus, is involved in memory consolidation in these sites.
Methods:
In this work, we have developed a partial least squares (PLS)-regression based two dimensional
quantitative structure-activity relationship (2D-QSAR) model using 1130 diverse chemical classes
of compounds with defined activity against the BuChE enzyme. Keeping in mind the strict Organization
for Economic Co-operation and Development (OECD) guidelines, we have tried to select significant
descriptors from the large initial pool of descriptors using multi-layered variable selection strategy using
stepwise regression followed by genetic algorithm (GA) followed by again stepwise regression technique
and at the end best subset selection prior to development of final model thus reducing noise in the
input. Partial least squares (PLS) regression technique was employed for the development of the final
model while model validation was performed using various stringent validation criteria.
Results:
The results obtained from the QSAR model suggested that the quality of the model is acceptable
in terms of both internal (R2= 0.664, Q2= 0.650) and external (R2
Pred= 0.657) validation parameters.
The QSAR studies were analyzed, and the structural features (hydrophobic, ring aromatic and hydrogen
bond acceptor/donor) responsible for enhancement of the activity were identified. The developed model
further suggests that the presence of hydrophobic features like long carbon chain would increase the
BuChE inhibitory activity and presence of amino group and hydrazine fragment promoting the hydrogen
bond interactions would be important for increasing the inhibitory activity against BuChE enzyme.
Conclusion:
Furthermore, molecular docking studies have been carried out to understand the molecular
interactions between the ligand and receptor, and the results are then correlated with the structural features
obtained from the QSAR models. The information obtained from the QSAR models are well corroborated
with the results of the docking study.
Funder
Indian Council of Medical Research
Publisher
Bentham Science Publishers Ltd.
Subject
Drug Discovery,General Medicine
Cited by
20 articles.
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