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Alzheimer's disease (AD) is a progressive neurological disorder affecting an estimated 10 million people worldwide. There is no cure for AD, and only a handful of drugs are known to provide some relief of the symptoms. The prescription drug donepezil has been widely used to treat to slow the progression and onset of the disease; however, the unpleasant side effects have paved the way to find alternative medicines. Many herbs are known to improve brain function, but evidence of medicinal plants that can treat AD is limited due to the lack of concrete rational evidences. Moreover, the traditional method of randomly screening plant extract against AD targets takes time and resources. In this study, a receptor-based  in silico  method has been implemented which serves to accelerate the process of identification of medicinal plants useful for treatment of AD. A database of natural compounds was compiled to identify hits against acetylcholinesterase (AChE). Receptor-based pharmacophore screening was performed, and selected hits were subjected to docking and molecular dynamics simulations. Molecular Mechanics/Generalized Born surface area (MM/GBSA) calculations were carried out to identify the best scoring hits further.  In vitro  assays were done for the plant extracts containing the top-scoring hits against AChE. Three plant extracts showed favorable inhibitory activity. Communicated by Ramaswamy H. Sarma

An in silico approach to identify potential medicinal plants for treating Alzheimer disease: a case study with acetylcholinesterase