Background Sepsis is a systemic inflammatory syndrome (SIRS) caused by acute microbial infection with high mortality rate. The role of tumour necrosis factor α (TNF-α)-induced necroptosis in promoting the pathophysiology of sepsis has been identified. Effective prevention of necroptosis is expected to improve the prognosis of sepsis patients. Methods We conducted bioinformatics prediction of candidate drugs by analyzing differentially expressed genes of sepsis patients extracted from GEO database, combining library of integrated network-based cellular signatures (LINCS) L1000 perturbation database. Biological experiments based on TNF-α-induced necroptosis in cellular and mouse model were performed to verify the protection of candidate drugs from SIRS. Cell viability was measured by CellTiter-Glo luminescent ATP assay. Effects of linifanib on necroptosis were investigated by western blotting, immunoprecipitation, and in vitro RIPK1 kinase assay. Survival curve analysis of SIRS mice treated by linifanib was performed. Results A total of 16 candidate drugs was screened out through bioinformatics analysis. Our experiments demonstrated that linifanib effectively protected cells from necroptosis and rescued the death of SIRS mice from shock induced by TNF-α. In vitro, linifanib directly suppressed RIPK1 kinase activity. In vivo, linifanib effectively reduced the overexpressed level of IL-6, a good marker of severity during severe sepsis, in the lung of SIRS mice. Conclusion We provide preclinical evidence for the potential clinical utility of linifanib in sepsis. Study of drug repositioning using bioinformatical predictions combined with experimental validations provides novel strategies for the development of sepsis drug.
Repositioning linifanib as a potent anti-necroptosis agent for sepsis