Network pharmacology to explore the anti-inflammatory mechanism of Xuebijing in the treatment of sepsis.

Abstract Background Xuebijing (XBJ) is a traditional Chinese patent medicine for sepsis. However, the mechanism of action (MoA) of XBJ on sepsis remain unclear. Purpose Elucidate the MoA of XBJ for treating sepsis based on network pharmacology. Study design Integrate computational prediction, experimental validation and literature reported clinical results analysis based on network pharmacology. Methods Computationally, representative compounds of XBJ were characterized by LC-MS/MS and the target profiles of each compound were identified using network-based method. Compounds from XBJ were compared with FDA approved drugs or experimental agents for sepsis by hierarchical clustering of target profile. Key biological functional modules of XBJ for treating sepsis were identified by enrichment analysis. Differential expressed analysis for each biological functional module was conducted from sepsis related public omics datasets. Herb-biological functional module network was constructed to reveal part of the traditional combinatorial rules of herbs for modules. Experimentally, the action of XBJ compounds on genes in biological functional module was validated by detecting quantitative transcriptional profiling and sepsis animal model. Clinically, combined with the clinical results recorded in literature, computational and experimental results were used to interpret the anti-inflammatory effect of XBJ for treating sepsis. Results The target profiles of compound cover most of the compound's related biomolecules reported in literature, which can characterize the comprehensive function of compound. XBJ has similar pharmacological effect as FDA approved drugs or experimental agents. Four key biological functional modules including inflammation, immune, cell apoptosis and coagulation of XBJ for treating sepsis were identified. Cell line experimental results show that part of ingredients in XBJ regulate the expression of genes in inflammation modules as predicted. Animal experiments show that compounds from XBJ could reduce the expression level of IL-1β. Combined with literature reported clinical results, XBJ was found to exert anti-inflammatory effect through regulating the NF-kappa B signaling pathway. Conclusion The network pharmacology framework integrating computational prediction, experimental validation and literature reported clinical results analysis provides a novel approach for analyzing MoA of XBJ for treating sepsis.