The Prediction of Quality Markers of Notopterygium Incisum Based on Mass Transfer Law and Network Pharmacology

Abstract Background To address medication safety concerns from depleted Notopterygium incisum Ting ex H. T. Chang (NI) resources and inconsistent quality, this study employed the Quality Markers (Q-Marker) concept of Traditional Chinese Medicine to screen potential Q-Markers via multi-step compositional transfer analysis and network pharmacology. Objective This study aimed to screen the Q-Markers of NI for treating cardiovascular diseases. Methods An approach integrating mass transfer analysis, network pharmacology, and High Performance Liquid Chromatography (HPLC) fingerprinting was employed. First, HPLC fingerprints of thirteen batches of NI were established. A representative batch was selected to prepare fresh medicinal materials, processed decoction pieces, and standard decoctions. Additionally, blood-absorbed components were collected, and fingerprints for all sample types were established. The transfer rates of seven index components (chlorogenic acid, nodakenin, ferulic acid, psoralen, bergapten, phenethyl ferulate, and isoimperatorin) were determined via similarity evaluation and least squares discriminant analysis. Network pharmacology and molecular docking were further used to analyze the associations between NI’s bioactive components and therapeutic targets for cardiovascular diseases. Results This study employed an integrated approach of HPLC fingerprinting, mass transfer analysis, network pharmacology, and molecular docking. After establishing HPLC fingerprints for thirteen NI batches, a representative batch was processed from fresh herbs, decoction pieces, standard decoctions, and blood-absorbed components for analysis, after which a determination was made for the transfer rates of seven index components and their associations with cardiovascular disease targets. Conclusion Chlorogenic acid, nodakenin, ferulic acid, phenethyl ferulate, and isoimperatorin are potential Q-Markers of NI for the treatment of cardiovascular diseases. Highlights In this study, mass transfer analysis, network pharmacology, and HPLC fingerprinting were integrated, combined with orthogonal partial least squares-discriminant analysis (OPLS-DA) and molecular docking. Potential Q-Markers of NI for the treatment of cardiovascular diseases were identified.