Elucidating the mechanism of plasticizer induced osteoporosis through network toxicology and molecular docking

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Target genes associated with osteoporosis were identified through differential expression analysis of various datasets by machine learning, enrichment analysis was performed to understand their biological functions, and the binding of plasticizers to target proteins was investigated using network toxicology and molecular docking techniques. Plasticizers may affect OP progression and alter expression levels in OP samples. Machine learning analysis identified six core target genes - CKM, TACR3, SOAT2, SGK1, ERAP2, and MMP12 - critical for plasticizer-induced OP. Molecular docking revealed specific binding interactions between plasticizers and target proteins.

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