SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test

基于机器学习算法、分子建模和体外试验,SRC 是牛蒡苷治疗三阴性乳腺癌的潜在靶点。

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Abstract

INTRODUCTION: This research explores the therapeutic potential of Arctigenin (AG) against triple-negative breast cancer (TNBC) and elucidates its underlying molecular mechanisms. METHODS: Potential targets of AG and TNBC-related genes were identified through public databases. By intersecting drug-specific and disease-related targets, key genes were selected for further analysis. Differential gene expression profiling and Weighted Gene Co-expression Network Analysis (WGCNA) were performed. Functional enrichment analysis was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. In vitro experiments including cell viability assays, cell cycle analysis, apoptosis detection, and Western blotting were performed on MDA-MB-453 and MDA-MB-231 cell lines. RESULTS: Our study identified 183 AG-related targets, 5,193 differentially expressed genes, and 6,173 co-expression module genes associated with TNBC. Machine learning algorithms pinpointed 4 hub genes from 28 intersecting targets. Molecular docking, Molecular dynamics (MD) and surface plasmon resonance (SPR) indicated a moderately strong interaction between AG and SRC kinase, where the oxygen atom of AG forms hydrogen bonds with the oxygen atom in M341 and the nitrogen atom in G344 of SRC. In vitro experiments confirmed that AG reduced the viability of MDA-MB-453 and MDA-MB-231 cells in a concentration-and time-dependent manner, leading S phase arrest and apoptosis. Western blotting indicated that AG significantly reduced the levels of Bcl-2, caspase-3, and caspase-9, as well as decreased SRC, p-PI3K-p85, p-AKT1, p-MEK1/2, and p-ERK1/2 expression in TNBC cells in a concentration dependent manner. CONCLUSION: AG exerts anti-TNBC effects by directly binding to SRC kinase, concurrently inhibiting both PI3K/AKT and MEK/ERK signaling pathways, ultimately leading to cell cycle arrest and apoptosis.

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