Revealing the molecular mechanisms underlying Xuebijing against sepsis and septic acute kidney injury via bioinformatics and experimental approaches
Abstract
Background Sepsis and its related complication acute kidney injury (septic-AKI) are associated with high mortality and morbidity, and have become a global health challenge. Xuebijing (XBJ) injection prepared from five traditional Chinese medicines (TCM) is commonly used for clinical treatment of sepsis and septic-AKI. Yet, the underlying therapeutic mechanism of XBJ is remain elusive. This study aims to unveil the underlying mechanisms of XBJ in treating sepsis and septic-AKI. Methods In this study, we used network pharmacology and molecular docking to screen the core drug-disease targets and predict the potential mechanism involving in XBJ against sepsis and septic AKI. Furthermore, in vitro experiments were performed to verify the predicted results and clarify the underlying mechanism. Results Five hub targets including MMP9, TNF, IL-6, STAT3 and TP53 were identified by constructing and analyzing protein-protein interaction network. Eight key active components linking to five hub targets were also reversely screened. The results of gene ontology (GO) and pathway enrichment analysis showed that on the list of top 10 significant GO terms and pathways, most were inflammatory signaling pathways. The molecular docking results suggested that eight active components more preferentially bound to MMP9 and TNFα with the highest affinity. In vitro, XBJ significantly decreased the mRNA and protein levels of IL-1β, IL-6, TNFα and MMP9 in HEK-293 cells exposed to lipopolysaccharides (LPS). Conclusions XBJ exerted therapeutic effects on sepsis and septic-AKI through suppression IL-1β/MMP9, IL-6/MMP9 and TNFα/MMP9 at both mRNA and protein level. This study provides a pharmacological basis for further validating the therapeutic mechanism of XBJ in treating sepsis and septic-AKI by in vitro and in vivo experiments.
Article Details
Authors (10)
Xing Li
Interdisciplinary Science Center, State Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management, Institute of Zoology
Kaiqi Ren
Michal R. Baran
Juan Tang
Le Wang
Gabriel Mbuta Tchivelekete
Yi Guo
Yang Bai
Weijian Yan
Xinhua Shu