Chemometric-guided chemical marker selection: A case study of the heat-clearing herb Scrophularia ningpoensis

The selection of medicinal plants’ chemical markers focuses on bioactivity as the primary goal, followed by the nature of secondary metabolites, their stability, and availability. However, herbal medicines are valued for their complex and holistic pharmacological effects. A correct chemical marker can be carefully selected by a systematic clarification of their chemical-biological relationships. In the current study, the multi-informative molecular networking (MIMN) approach was employed to construct the anti-inflammatory metabolomic pattern of a heat-clearing herb, Scrophularia ningpoensis Hemsl. (S. ningpoensis). The MIMN molecular families characterized by cinnamic acid glycosides showed a higher bioactivity score compared with the other two major chemical classes (iridoid glycosides and iridoid-cinnamic acid glycosides). The Global Natural Product Social Molecular Networking (GNPS) and Reaxys database were used to assist in the putative annotation of eighteen metabolites from the bioactive and non-bioactive molecular families. The anti-inflammatory validation step was based on the detection of reactive oxygen species (ROS) generation by activated human neutrophils. All compounds from the bioactive MIMN molecular families dose-dependently inhibited the total ROS generation promoted by fMLF (IC50: 0.04–0.42 μM), while the compounds from non-bioactive MIMN clusters did not show any significant anti-inflammatory effect. The ROS-dependent anti-inflammatory activity of these cinnamic acid glycosides was attributed to their oxygen radical scavenging ability. The most abundant cinnamic acid glycoside, angoroside C (IC50: 0.34 μM) was suggested to be selected as a chemical marker for S. ningpoensis. In this study, the MIMN platform was applied to assist in the chemical marker selection of S. ningpoensis. The correct selection of markers will aid in the compilation and revision of herbal monographs and pharmacopeias resulting in the precise analysis and classification of medicinal plants on a scientific basis.