GLOBAL METABOLITE PROFILING AND NETWORK PHARMACOLOGY OF TRIPHALA IDENTIFIES NEUROMODULATORY RECEPTOR PROTEINS AS POTENTIAL TARGETS

Triphala is an herbal formulation widely used in Ayurvedic medicine as a rejuvenation and revitalization therapy. Its constituents include a mixture of dried extracts from Phyllanthus emblica , Terminalia chebula and Terminalia bellirica. This formulation has been extensively investigated for its anti-cancer, anti-caries, anti-microbial, immunomodulatory and hypolipidemic activities. Currently, the activity of Triphala is attributed to the composition of its individual constituents. However, its composition has not been comprehensively characterized. In this study, we employed a mass spectrometry-based strategy to globally profile the constituent metabolites in Triphala. Using methanolic and aqueous extraction methods, we identified 1,897 metabolites in Triphala. We identified previously known Triphala metabolites such as gallic acid derivatives, chebulinic acid, syringic acid, ascorbic acid derivatives and epicatechin. We also identified several metabolites that were not previously reported from Triphala extract including metabolites from isoquinoline alkaloids, flavonoid, stilbenoid, diarylheptanoid and gingerol and indole alkaloid classes. Pathway analysis revealed enrichment of thiamine metabolism, tyrosine metabolism, lysine biosynthesis and isoquinoline alkaloid biosynthesis pathways. Furthermore, prediction of binding targets of Triphala metabolites using a network pharmacology approach resulted in the identification of 387 potential protein targets in human, mammalian and microbial species suggesting potential anti-microbial, anti-cancer, and nootropic activities. Protein targets of Triphala include members of neuromodulatory classes including opioid receptor, 5-Hydroxytryptamine receptor, alpha adrenergic receptor, glutamate receptor and kinases including mTOR, p38, Aurora kinase B AXL, VEGFR, PI3K, PKC among others. The metabolite profiling of Triphala is a proof-of-principle study that will serve to benchmark, standardize and characterize other traditional formulations.  Keywords : Traditional medicine; metabolic fingerprinting; drug benchmarkin