Ayurveda and in silico Approach: A Challenging Proficient Confluence for Better Development of Effective Traditional Medicine Spotlighting Network Pharmacology.
10.1007/s11655-022-3584-x
- Author:
Rashmi SAHU
1
;
Prashant Kumar GUPTA
1
;
Amit MISHRA
2
;
Awanish KUMAR
3
Author Information
1. Department of Balroga, Shri NPA Govt. Ayurveda College, Raipur, Chhattisgarh, 492010, India.
2. Cellular and Molecular Neurobiology Unit, Indian Institute of Technology, Jodhpur, Rajasthan, 342037, India.
3. Department of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh, 492010, India. drawanishkr@gmail.com.
- Publication Type:Review
- Keywords:
Ayurveda;
challenge;
confluence;
effective therapeutics;
in silico approach
- From:Chinese journal of integrative medicine
2022;():1-11
- CountryChina
- Language:English
-
Abstract:
Coalescence of traditional medicine Ayurveda and in silico technology is a rigor for supplementary development of future-ready effective traditional medicine. Ayurveda is a popular traditional medicine in South Asia, emanating worldwide for the treatment of metabolic disorders and chronic illness. Techniques of in silico biology are not much explored for the investigation of a variety of bioactive phytochemicals of Ayurvedic herbs. Drug repurposing, reverse pharmacology, and polypharmacology in Ayurveda are areas in silico explorations that are needed to understand the rich repertoire of herbs, minerals, herbo-minerals, and assorted Ayurvedic formulations. This review emphasizes exploring the concept of Ayurveda with in silico approaches and the need for Ayurinformatics studies. It also provides an overview of in silico studies done on phytoconstituents of some important Ayurvedic plants, the utility of in silico studies in Ayurvedic phytoconstituents/formulations, limitations/challenges, and prospects of in silico studies in Ayurveda. This article discusses the convergence of in silico work, especially in the least explored field of Ayurveda. The focused coalesce of these two domains could present a predictive combinatorial platform to enhance translational research magnitude. In nutshell, it could provide new insight into an Ayurvedic drug discovery involving an in silico approach that could not only alleviate the process of traditional medicine research but also enhance its effectiveness in addressing health care.
