Network Pharmacology and Machine Learning Reveal Salidroside’s Mechanisms in Idiopathic Pulmonary Fibrosis Treatment

作者：Chenchun Ding, Zhenzhen Guo, Quan Liao, Renjie Zuo, Junjie He, Ziwei Ye, Weibin Chen · 发表于：Journal of Inflammation Research · 年份：2024 · DOI：10.2147/jir.s493171 · 被引用次数：7 · 研究领域：Medicinal Plants and Bioactive Compounds、Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis、Magnesium in Health and Disease

Purpose: Idiopathic pulmonary fibrosis (IPF) is an irreversible respiratory disease. In this study, we evaluated the efficacy of salidroside (SAL), the main component of Rhodiola rosea, in treating IPF. Methods: The pharmacological effects of SAL against epithelial-mesenchymal transition (EMT) and IPF were assessed through in vivo and in vitro experiments. Targets for SAL in treating IPF were identified from various databases and a PPI network was constructed. Functional analyses of target genes were performed using GO, KEGG, DO, and GSEA. Core target genes were identified using LASSO logistic regression and support vector machine (SVM) analysis, followed by molecular docking simulations. Predicted targets and pathways were validated through Western blotting, qRT-PCR, and IHC. Results: Our results demonstrated that SAL ameliorated alveolar epithelial cells (AECs) EMT and mitigated bleomycin -induced pulmonary fibrosis. Through network pharmacology, we identified 74 targets for SAL in the treatment of IPF (P FDR < 0.05) and analyzed their biological functions. Based on these findings, we further applied machine learning techniques to narrow down 9 core targets (P FDR < 0.05). Integrating the results from molecular docking, KEGG, and GSEA analyses, we selected three key targets—IGF1, hypoxia-inducible factor 1-alpha (HIF-1α), and MAPK (P FDR < 0.05)—for further investigation. Our study revealed that SAL inhibits the IGF1 signaling pathway, thereby improving AECs senescence and ...