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.
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Acknowledgments
CGM is grateful to Amrita Centre for Nanosciences and Molecular Medicine, Amrita Vishwa Vidyapeetham (Amrita University) for computational infrastructure support. JJ is supported by a senior research fellowship (Order No:45/16/2011/IMM-BMS) from a council of scientific and industrial research (CSIR), India.
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Sneha Patil and Ankit Tyagi contributed equally to this work.
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Patil, S., Tyagi, A., Jose. , J. et al. Integration of common feature pharmacophore modeling and in vitro study to identify potent AChE inhibitors. Med Chem Res 25, 2965–2975 (2016). https://doi.org/10.1007/s00044-016-1716-6
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DOI: https://doi.org/10.1007/s00044-016-1716-6