Abstract
The single drug/single target/single disease tactic to medicine detection currently faces many challenges in terms of welfare, efficiency and sustainability. Network biology and multipharmacology approaches have recently gained acceptance as approaches for omics documents incorporation and multi-target drug development, respectively. Combining these two approaches has created a new model termed network pharmacology (NP) that examines the effects of medications on both interaction and disease. Ayurveda, traditional Indian medicine, uses a scientific formula that contains many ingredients and numerous bioactive composites. Though, the scientific basis and methods are still largely unexplored. Network pharmacology is a prediction tool that helps in predicting the bioactives from different databases, respective genes from databases which are expressed during the disease. The genes are also ranked from cytohubba and genes with greater number have greater interactions with other genes. The mechanism can be predicted from different pathways like KEGG pathway. From the obtained data a network can be constructed using cytoscape and represented.
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