Multivariate Statistical Analysis of Metabolites in Anisodus tanguticus (Maxim.) Pascher to Determine Geographical Origins and Network Pharmacology

Abstract

Anisodus tanguticus (Maxim.) Pascher, has been used for the treatment of septic shock, analgesia, motion sickness, and anesthesia in traditional Tibetan medicine for 2,000 years. However, the chemical metabolites and geographical traceability and their network pharmacology are still unknown. A total of 71 samples of A. tanguticus were analyzed by Ultra–Performance Liquid Chromatography Q–Exactive Mass Spectrometer in combination with chemometrics developed for the discrimination of A. tanguticus from different geographical origins. Then, network pharmacology analysis was used to integrate the information of the differential metabolite network to explore the mechanism of pharmacological activity. In this study, 29 metabolites were identified, including tropane alkaloids, hydroxycinnamic acid amides and coumarins. Principal component analysis (PCA) explained 49.5% of the total variance, and orthogonal partial least-squares discriminant analysis (OPLS–DA) showed good discrimination (R2Y = 0.921 and Q2 = 0.839) for A. tanguticus samples. Nine differential metabolites accountable for such variations were identified through variable importance in the projection (VIP). Through network pharmacology, 19 components and 20 pathways were constructed and predicted for the pharmacological activity of A. tanguticus. These results confirmed that this method is accurate and effective for the geographic classification of A. tanguticus, and the integrated strategy of metabolomics and network pharmacology can explain well the “multicomponent—-multitarget” mechanism of A. tanguticus.