Integrating Network Pharmacology and an Experimental Model to Investigate the Effect of Zhenwu Decoction on Doxorubicin-Induced Heart Failure

Author:

Hu Yiran1ORCID,Qu Huiyan2ORCID,Zhou Hua2ORCID

Affiliation:

1. Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

2. Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

Abstract

Background: Doxorubicin-induced heart failure is a clinical problem that needs to be solved urgently. Previous studies have confirmed that Zhenwu Decoction, a traditional Chinese medicine compound, can effectively improve chronic heart failure. However, its interventional effect on Doxorubicin-induced heart failure has not yet been investigated. In this study, we investigated the therapeutic effect and potential mechanism of Zhenwu Decoction on Doxorubicininduced heart failure through animal experiments and network pharmacology. Objective: The study aimed to investigate the therapeutic effect and potential mechanism of Zhenwu Decoction (ZWD) on Doxorubicin-induced heart failure. Methods: A heart-failure mouse model was established in 8-week-old male C57/BL6J mice using Doxorubicin, and the mice were then treated with ZWD for a 4-week period. Firstly, network pharmacology was conducted to explore the potential active components and molecular mechanisms of ZWD on Doxorubicin-induced heart failure. Next, we conducted an in vivo study on the effect of ZWD on Doxorubicin-induced heart failure. After the intervention, the cardiac function and levels of cardiac function injury marker in serum were measured to evaluate the therapeutic effect of ZWD on cardiac function. Then HE staining and Masson staining were used to evaluate the effect of ZWD on myocardial pathology, and biochemical method was used to detect the effect of ZWD on total antioxidant capacity and inflammation, and finally, Western blot was used to detect TGFβ, Smad-3, and collagen I protein expression levels to evaluate its effect on myocardial fibrosis. Results: In Doxorubicin-induced heart failure mice, ZWD improved cardiac function and reduced the levels of CK-MB, NT-proBNP, and BNP in the serum, improved myocardial pathology, and reduced TGFβ, Smad-3 and collagen I protein expression levels to improve myocardial fibrosis. Network pharmacological analysis showed that ZWD has 146 active ingredients and 248 candidate targets. Moreover, 2,809 genes were found to be related to Doxorubicin-induced heart failure, and after screening, 74 common targets were obtained, mainly including IL-6, AKT1, caspase-3, PPARG, PTGS2, JUN, HSP90AA1, and ESR1. KEGG analysis confirmed that PI3K/AKT and IL- 6/NF-κB signaling pathways were the two main pathways underlying the cardioprotective effects of ZWD. Finally, in vivo experiments showed that ZWD improved the total antioxidant capacity, reduced the SOD level, increased the protein expression of PI3K, Akt, Bcl-2, Bax, and caspase-3, reduced the levels of TNF-α, IL-6, and IL-1β, and decreased the NF-κB p65, IL-6, and TNF-α protein expression levels. Conclusion: In Doxorubicin-induced heart-failure mice, Zhenwu Decoction improved the cardiac function and myocardial pathology, and improved myocardial fibrosis through the TGFβ/Smad-3 signaling pathway. According to the prediction of network pharmacology, in vivo experiments demonstrated that Zhenwu Decoction can improve the oxidative stress response, improve myocardial cell apoptosis through the PI3K/AKT signaling pathway, and improve myocardial inflammation by reducing the levels of inflammatory factors and by reducing the protein expression of NF- κB p65, IL-6, and TNF-α.

Funder

Construction of atrial fibrillation specific disease database

Three years action plan of Shanghai Shenkang Medical Development Center

Science and technology support project of Shanghai Municipal Commission of science and Technology

Shanghai Shenkang medical development center emerging frontier technology joint research project

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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