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Abstract

Network Pharmacological Evaluation of Glycyrrhiza glabra for its Activity against Neuropathic Pain

Author(s): Tanmayee Amit Joshi and Pratima Arun Tatke*
Department of Pharmacology, 1Department of Pharmaceutical Chemistry, CU Shah College of Pharmacy, Shreemati Nathibai Damodar Thackersey (SNDT) Women’s University, Mumbai, Maharashtra 400049, India

Correspondence Address:
Pratima Tatke, Department of Pharmaceutical Chemistry, CU Shah College of Pharmacy, Shreemati Nathibai Damodar Thackersey (SNDT) Women’s University, Mumbai, Maharashtra 400049, India, E-mail: [email protected]


Glycyrrhiza glabra (licorice), is used for therapeutic purposes since ages. Neuropathic pain is a disease with complex pathophysiology, involving dysfunction in multiple ion channel receptors such as sodium, transient receptor potential channels, neurotransmitters, inflammatory mediators and reactive oxygen species. Network pharmacology is newly emerging approach dealing with understanding mechanism of actions of druggable molecules with the multiple targets. This approach is suitable to deal with AYUSH based medicines such as extracts containing many bioactives, acting on multiple targets. The aim of the present study is to construct a network of licorice to predict its actions against neuropathic pain. Various knowledge databases were used for collecting information regarding bioactives, their targets and genes associated with these targets or pathophysiology of neuropathic pain. These databases include Dr. Duke's Phytochemical and Ethnobotanical Database, PubMed, Google scholar, PubChem, BindingDB, Kyoto encyclopedia of genes and genomes, DisGeNET and Therapeutic Target Database. The network was constructed using Cytoscape3.7.2. 19 bioactive were shortlisted by extensive search having targets on humans and rats using BindingDB. These targets were searched on Kyoto encyclopedia of genes and genomes, DisGeNET for their association with neuropathic pain. Targets were shown to be part of pathways of neuropathic pain, helping to predict mechanism of action of bioactives. Hence, this approach can prove helpful in modern pharmacological research.

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