Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease.
Keywords: medicinal plants, metabolomics, phytochemical profiling, LC-MS, GC-MS, network biology, polypharmacology
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