Abstract

Traditional Chinese medicines (TCMs) have been widely used in Asian countries for thousands of years due to their supreme quality and good clinical efficacy. However, the increasing demand for TCMs in recent decades warrants effective quality control methodology to avoid clinical problems. Therefore, comprehensive quality evaluation systems should be established for ensuring TCM's quality, in terms of chemical components, as well as bioactivity for identifying quality markers in TCM and developing suitable analytical methods for quality control. In this study, we selected Sophora flavescens (S. flavescens) as the research object and developed a novel integrated strategy combining metabolomics and network pharmacology to explore the quality markers. Firstly, we determined the targeted metabolomic profiles of seventy-four batches of S. flavescens (aged from 1 to 6 years) by UHPLC/QE-MS. Six potential markers were successfully screened, quantified and reverse-verified as the most influential effective compounds by UHPLC/QE-MS and multivariate statistical analysis. Secondly, the network of "components-targets-pathways" was constructed, and the pharmacological activities of six potential markers were predicted. Finally, we determined the anti-tumor activity of six flavonoids (kurarinone, norkurarinone, kuraridin, kushenol N, trifolirhizin, and genistein) as the quality markers for Sophora flavescens, evaluated their pharmacokinetic profiles and reviewed their existing pharmacological researches. Thus, integrated metabolomics and network pharmacology technology were applied for the effective discovery of quality markers of Chinese material medica.

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