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

Abstract

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

Keywords:

• Natural products
• Alzheimer’s disease
• acetylcholinesterase
• pharmacophore
• molecular docking
• molecular dynamics simulations
• MM/GBSA

Acknowledgements

Financial support from the DBT-RA Program in Biotechnology and Life Sciences is gratefully acknowledged by Angamba Meetei Potshangbam. The authors also acknowledged computational facilities provided by BIF, Manipur University. Aslam Khan thanks the Researchers Supporting Project (RSP-2020/127), King Saud University, Riyadh, Saudi Arabia for the support.

Author contributions

Conceptualization, A.P. and N.P.; methodology, A.P.; A.N. and T.A.; software, A.P.; validation, A.P.; A.N. and T.A.; formal analysis, A.P.; H.R.; R.R.; R.L; N.P. and A.K.; investigation, A.P.; resources, A.P.; data curation, A.P.; writing – original draft preparation, A.P.; writing – review and editing, H.R.; R.R.; R.L.; N.P. and A.K.; visualization, A.P.; supervision, A.P. and N.P.; project administration, A.P. and N.P; funding acquisition, A.P.

Disclosure statement

The authors have no conflict of interest.

Additional information

Funding

This research was funded by Department of Science and Technology, India, under the SYST Grant No: SP/YO/071/2017(G). This research was also supported by the Researchers Supporting Project (RSP-2020/127), King Saud University, Saudi Arabia.