Current medicinal chemistry · 2026
A Combined Network Toxicology and Docking Study to Identify Putative Molecular Targets Linking Styrene Exposure to Atherosclerosis.
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Yan Shuai, Shen Geng, Huang Yu-Qing, He Guo-Dong
Аннотация
BACKGROUND: Styrene is a ubiquitous volatile organic compound linked to hematologic and vascular alterations; however, the molecular mechanisms connecting exposure to atherosclerosis remain poorly characterized.
METHODS: We integrated peripheral blood mononuclear cell transcriptomic profiles (GSE23746) with toxicogenomic data from the Comparative Toxicogenomics Database, applying support vector machine recursive feature elimination and least absolute shrinkage and selection operator machine learning algorithms to identify core targets at the styrene-atherosclerosis intersection. Immune infiltration was assessed using CIBERSORT and single-sample gene set enrichment analysis, and molecular docking evaluated binding potential.
RESULTS: Four model genes-CCND3, CCR1, MYC, and MYD88-were identified and constituted a diagnostic signature with high accuracy (area under the curve > 0.9). These genes were enriched in IL-17 and NF-κB inflammatory pathways and correlated with distinct immune cell alterations, particularly neutrophils and T cell subsets. Molecular docking predicted direct, moderate-affinity binding of styrene to CCND3 (Vina score = -6.4 kcal/mol), involving multiple contacts within the cyclin domain.
DISCUSSION: The convergence of transcriptomic screening and molecular docking identifies CCND3 as a putative target for styrene-protein interaction and suggests a mechanistic hypothesis linking styrene to atherosclerosis via inflammatory and immune dysregulation. The computational framework provides a basis for future experimental validation.
CONCLUSION: This computational framework generates the hypothesis that styrene may contribute to atherosclerosis through coordinated perturbations of immune signaling and cell cycle regulation, with CCND3 representing a candidate molecular target for future experimental validation in styrene-exposed populations.
METHODS: We integrated peripheral blood mononuclear cell transcriptomic profiles (GSE23746) with toxicogenomic data from the Comparative Toxicogenomics Database, applying support vector machine recursive feature elimination and least absolute shrinkage and selection operator machine learning algorithms to identify core targets at the styrene-atherosclerosis intersection. Immune infiltration was assessed using CIBERSORT and single-sample gene set enrichment analysis, and molecular docking evaluated binding potential.
RESULTS: Four model genes-CCND3, CCR1, MYC, and MYD88-were identified and constituted a diagnostic signature with high accuracy (area under the curve > 0.9). These genes were enriched in IL-17 and NF-κB inflammatory pathways and correlated with distinct immune cell alterations, particularly neutrophils and T cell subsets. Molecular docking predicted direct, moderate-affinity binding of styrene to CCND3 (Vina score = -6.4 kcal/mol), involving multiple contacts within the cyclin domain.
DISCUSSION: The convergence of transcriptomic screening and molecular docking identifies CCND3 as a putative target for styrene-protein interaction and suggests a mechanistic hypothesis linking styrene to atherosclerosis via inflammatory and immune dysregulation. The computational framework provides a basis for future experimental validation.
CONCLUSION: This computational framework generates the hypothesis that styrene may contribute to atherosclerosis through coordinated perturbations of immune signaling and cell cycle regulation, with CCND3 representing a candidate molecular target for future experimental validation in styrene-exposed populations.