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Research Articles

Network pharmacological evaluation of Withania somnifera bioactive phytochemicals for identifying novel potential inhibitors against neurodegenerative disorder

, , , &
Pages 10887-10898 | Received 12 May 2021, Accepted 29 Jun 2021, Published online: 19 Jul 2021
 

Abstract

Neurodegenerative disorders are illnesses that are responsible for neuronal cell death and resulting in lifelong cognitive problems. Due to their unclear mechanism, there are no effective drugs available for the treatment. For a long time, herbal drugs have been used as a role model in the field of the drug discovery process. Withania somnifera (Ashwagandha) in the Indian medicinal system (Ayurveda) is used for several neuronal disorders like insomnia and memory loss for decades. This study aims to identify active components of W. somnifera (WS) as potential inhibitors for the treatment of neurodegenerative diseases (ND). To fulfill this objective, Network pharmacology approach, gene ontology, pharmacokinetics analysis, molecular docking, and molecular dynamics simulation (MDS) studies were performed. A total of 77 active components in WS, 175 predicted neurodegenerative targets of WS, and 8085 ND-related targets were identified from different databases. The network analysis showed that the top ten targets APP, EGFR, MAPK1, ESR1, HSPA4, PRKCD, MAPK3, ABL1, JUN, and GSK3B were found as significant target related to ND. On the basis of gene ontology and topology analysis results, APP was found as a significant target related to Alzheimer’s disease pathways. Molecular docking results found that Anahygrine, Cuscohygrine, Isopelletierine, and Nicotine showed the best binding affinities −5.55, −4.73, −4.04, and −4.11 Kcal/mol. Further, MDS results suggested that Isopelletierine and Nicotine could be used as potential inhibitors against APP protein and could be useful for the treatment of Alzheimer’s disease.

Communicated by Ramaswamy H. Sarma

Acknowledgments

Authors are thankful to the Ministry of Education, India for providing fellowship and Central Computing Facility (CCF) of IIITA.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Science and Engineering Research Borad (SERB), DST, India (Project No: EEQ/2018/000486).

Notes on contributors

Sangeeta Singh

SS conceived and designed this study. SP performed analysis and wrote the manuscript. AG and PC helped in performing analysis. AC and SS did the proofreading.

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