Chemotherapy with anthracyclines can cause cardiotoxicity, possibly leading to stopping treatment in some cancer patients. In cardio-oncology research, preventing and minimizing anthracycline-induced cardiotoxicity (AIC) is a hot issue. For the treatment of AIC, calycosin (CA), an isoflavone component in astragali radix (AR), has become a research focus. However, the elaborate mechanisms of calycosin treating AIC remain to be unrevealed.
To explore the effects of CA on AIC through multiple dimensions concerning network pharmacology, molecular docking, and experimental evaluations.
The study evaluated calycosin's potential targets and mechanisms for treating AIC using network pharmacology and molecular docking. The candidate genes/targets of CA and AIC were screened using the online-available database. Protein-protein interactions (PPI) between the common targets were constructed using the STRING platform, and the results were then visualized using Cytoscape. Molecular docking was used to evaluate the strength of the binding force between CA and the common targets. The possible pharmacological mechanisms of CA were explained by pathway enrichment and GSEA. Subsequently, the candidate targets were identified
Network pharmacology effectively discovered the CA's multitarget intervention in AIC, including TNF, ABCC1, TOP2A, ABCB1, and XDH. CA binds to the ATP-binding cassette subfamily B member 1(ABCB1) had the highest binding energy (−7.5 kcal/mol) according to the molecular docking analysis and was selected and visualized for subsequent analysis. In vitro experiments showed that ABCB1 exhibited significant time-curve changes under different doses of doxorubicin (DOX) compared with DMSO control experiments. The anti-AIC pharmacological mechanism of CA were revealed by highlighting the biological processes of oxidative stress (OR) and inflammation.
We employed a practicable bioinformatics method to connect network and molecular docking to determine the calycosin's therapeutic mechanism against AIC and identified some bioinformatics results in