Molecular modelling studies on flavonoid derivatives as dual site inhibitors of human acetyl cholinesterase using 3D-QSAR, pharmacophore and high throughput screening approaches

Alzheimer's disease (AD) is a multi-factorial neurodegenerative disease that affects millions of elderly people worldwide. Due to its massive occurrence and severity, there is continuing and compelling need for the development of novel and effective drugs for improved treatment of AD. Since AD is characterized by the deficiency in cholinergic neurotransmission, acetyl cholinesterase (AChE) has been considered as a promising drug target. Herein we triggered our effort to design novel and potential inhibitors of AChE using a set of 24 flavonoid compounds having inhibitory activity against AChE. We carried out 3D-QSAR-based and pharmacophore-based identification of novel natural lead candidates. The 3D-QSAR model obtained using partial least square regression showed satisfactory parametric values (r (2) = 0.8227, q (2) = 0.6833 and pred-r (2) = 0.7893). Amongst total 14 pharmacophore hypothesis generated the one possessing following five features: one hydrogen bond acceptor, two hydrophobic regions and two aromatic rings, was considered to be the best pharmacophore hypothesis. Above-described robust and validated 3D-QSAR and pharmacophore models were used for carrying out prospective generic prediction and virtual screening on large natural compound libraries. The screened molecules from both the approaches were subjected for further docking analysis to reveal the binding modes of actions of these ligands. All the ligands were found to bind with both catalytic and anionic subsite of AChE. The molecular insights obtained from this study will be of high value for design and development of novel drugs for AD, possessing improved binding properties and low toxicity to human.