Jatamansinol from Nardostachys jatamansi: a multi-targeted neuroprotective agent for Alzheimer’s disease

Abstract

Alzheimer’s disease (AD) is a multifactorial progressive and irreversible neurodegenerative disorder characterized by severe memory impairment and cognitive disability in the middle and old-aged human population. There are no proven drugs for AD treatment and prevention. In Ayurveda, medhya plants are used to prepare Rasayana, and its consumption improves memory and cognition. Nardostachys jatamansi (D.Don) DC is a medhya plant used in traditional medicine to treat neurological disorders, and its unique pyranocoumarins can be a potential drug candidate for AD. Given its traditional claims, this study aims to find the multi-target potential efficacy of the ligands (drug molecules) against the AD from N. jatamansi pyranocoumarins using computational drug discovery techniques. Drug likeliness analysis confirms that pyranocoumarins of N. jatamansi, such as seselin, jatamansinol, jatamansine, jatamansinone, and dihydrojatamansin are probable drug candidates for AD. Molecular docking, molecular dynamic simulations, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis confirm that dihydrojatamansin inhibits acetylcholinesterase (AChE), and jatamansinol inhibits butyrylcholinesterase (BuChE), glycogen synthase kinase 3β (GSK3β), and kelch-like ECH-associating protein 1 (Keap1) AD therapeutic targets. Therefore, this study provides potential multi-target inhibitors that would further validate experimental studies, leading to new treatments for AD.

Communicated by Ramaswamy H. Sarma

Keywords:

• Nardostachys jatamansi
• pyranocoumarins
• Alzheimer’s disease
• molecular docking
• Ayurveda

Acknowledgment

The authors are thankful to the Central University of Kerala authorities for providing facilities and Kerala State Council for Science, Technology, and Environment (KSCSTE), CSIR-UGC, CSIR-SRF for the research fellowships. Finally, the authors are grateful to the anonymous reviewers for their valuable, constructive comments and suggestions to improve the quality of this manuscript. Special thanks to Schrodinger, Bangalore for providing required software for the work.

Disclosure statement

No potential conflict of interest was reported by the authors.