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

Abstract

Objective: This study investigated the effects of plasticizers (phthalates) on the pathogenesis of osteoporosis (OP) and the associated molecular mechanisms, especially the interaction of plasticizers with key pathways.

Methods: We performed differential expression analysis of different datasets by machine learning to identify target genes associated with OP. And, we also investigated the binding of plasticizers to target proteins using network toxicology and molecular docking techniques.

Results: A total of 29 genes are potential targets associated with plasticizer-induced OP. Subsequently, machine learning analysis identified six core target genes as key genes for plasticizer-induced OP. Among them, the up-regulated genes were CKM and SOAT2, and the down-regulated genes were TACR3, SGK1, ERAP2, and MMP12 (P＜0.05). Molecular docking revealed the specific binding effect between plasticizers and target proteins.

Conclusion: This study demonstrates that plasticizers may influence the pathogenesis of OP by targeting specific genes and pathways. And the molecular docking simulations indicate a distinct binding specificity between plasticizers and target proteins. These results provide a foundation for further investigation into the mechanisms by which plasticizers affect bone health. Future research should focus on the dose-response relationship between plasticizer exposure and the risk of OP, and explore potential intervention measures to mitigate the adverse effects of plasticizers on bone health.

Keywords: Bioinformatics; Machine learning; Molecular docking; Osteoporosis; Phthalates; Plasticizers.