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Integration of Common Feature Pharmacophore Modeling and in Vitro Study to Identify Potent AChE Inhibitors

Publication Type : Journal Article

Thematic Areas : Nanosciences and Molecular Medicine

Publisher : Medicinal Chemistry Research.

Source : Medicinal Chemistry Research, Volume 25, Number 12, p.2965–2975 (2016)

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Campus : Kochi

School : Center for Nanosciences

Center : Amrita Center for Nanosciences and Molecular Medicine Move, Nanosciences

Department : Nanosciences and Molecular Medicine, Nanosciences

Verified : Yes

Year : 2016

Abstract : Alzheimer's disease is a progressive neurodegenerative disorder arising due to genetic and non-genetic causes. One of the major therapies adapted for symptomatic Alzheimer's disease is by targeting acetylcholinesterase enzyme based on the cholinergic hypothesis. Acetylcholinesterase is a substrate-specific enzyme that degrades the neuro-transmitter acetylcholine. An optimum level of acetylcholine should be maintained in the brain for its proper function. In order to identify potent and selective acetylcholinesterase inhibitors we adopted an integrated in silico and bioassay methodologies. In silico approach involves creating chemical features based 3D-pharmacophore models using AChE specific inhibitors. This model was then used for sequential virtual screening from the small molecule databases. Finally, five molecules were selected on the basis of the best docking scores and pharmacokinetics properties. These molecules were subjected to docking analysis with the recently solved crystal structure of human acetylcholinesterase enzyme, in order to reveal its binding mode and interactions at the dual binding sites of the enzyme. The acetylcholinesterase enzyme inhibitory activity of these five lead molecules was further assessed by in-vitro analysis.

Cite this Research Publication : S. Patil, Tyagi, A., Jose., J., Krishnakumar N. Menon, and Dr. Gopi Mohan C., “Integration of Common Feature Pharmacophore Modeling and in Vitro Study to Identify Potent AChE Inhibitors”, Medicinal Chemistry Research, vol. 25, pp. 2965–2975, 2016.

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