Objective To screen the active compounds in Sini Decoction showing the potential to inhibit tumor necrosis factor α（TNFα） to alleviate Doxorubicin（DOX）-induced heart failure. Methods A chemical database of Sini Decoction was constructed from literature research. The generated pharmacophore models based on TNF-α used to screen active ingredients of Sini Decoction in the database by Discovery Studio 2.5. Molecular docking by Autodock 4.2 was adopted to demonstrate the hit compounds＇ affinities with TNFα. Furthermore, DOX-induced heart failure model on H9c2 cell line was constructed and cell viability was detected by CCK-8 to validate the therapeutic effect of potential active compounds. Results The higenamine showed potential cardiovascular protective effect through virtual screening. And the activity was identified in vitro. Conclusion In this study, we found that higenamine may inhibit TNF-ɑ through virtual docking and validated that higenamine may have the potential of treatment for heart failure in the model of doxorubicin-induced myocardial toxicity to H9c2 cells.
Hyperlipidemia is considered to be a high lipid level in blood,can induce metabolic disorders and dysfunctions of the body,and results in some severe complications.Therefore,hunting for some metabolite markers and clarifying the metabolic pathways in vivo will be an important strategy in the treatment and prevention of hyperlipidemia.In this study,a rat model of hyperlipidemia was constructed according to histopathological data and biochemical parameters,and the metabolites of serum and urine were analyzed by UPLC-Q-TOF/MS.Combining pattern recognition and statistical analysis.19 candidate biomarkers were screened and identified.These changed metabolites indicated that during the development and progression of hyperlipidemia,energy metabolism,lipid metabolism,amino acid metabolism and nucleotide metabolism were mainly disturbed,which are reported to be closely related to diabetes,cardiovascular diseases,etc.This study demonstrated that a UPLC-Q-TOF/MS based metabolomic approach is useful to profile the alternation of endogenous metabolites of hyperlipidemia.
