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<p>Liver hepatocellular carcinoma (LIHC) remains a critical health challenge with limited treatments. This study employed network toxicology and molecular docking to investigate how polycyclic aromatic hydrocarbons (PAHs), as environmental carcinogens, promote LIHC. By analyzing TCGA LIHC data and screening genes via the Comparative Toxicogenomics Database, 1,817 key PAH-LIHC-related genes were identified. Enrichment analyses revealed associated biological pathways, and a protein–protein interaction network pinpointed 321 MCODE-derived functional module genes. A prognostic risk model based on 14 model genes was developed, demonstrating high accuracy in predicting 1&#xa0;year survival for LIHC patients. Immune infiltration analysis showed distinct profiles between high- and low-risk groups. Molecular docking showed favorable docking scores and potential binding conformations of PAHs to key genes (ANXA5, LOX, HSP90AA1). Among these, the ANXA5–805-PAH complex was further subjected to a 50&#xa0;ns molecular dynamics simulation to describe its short-term dynamic behavior. The results provide exploratory computational clues for PAH-related candidate targets, but further confirmation is required through rigorous docking protocol validation, repeated simulations, and experimental studies. This research provides a PAH-related prognostic model and elucidates molecular mechanisms of environmental toxin-driven liver cancer.</p>

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Assessing the impact of polycyclic aromatic hydrocarbon exposure on liver cancer using network toxicology and molecular docking

  • 期刊论文

  • 发表日期：

    2026年6月28日

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  • Qi Wang,
  • Shilei Rao,
  • Yao Lu,
  • Yuanying Li,
  • Jianghao Zhang,
  • Lixin Wan

摘要

Liver hepatocellular carcinoma (LIHC) remains a critical health challenge with limited treatments. This study employed network toxicology and molecular docking to investigate how polycyclic aromatic hydrocarbons (PAHs), as environmental carcinogens, promote LIHC. By analyzing TCGA LIHC data and screening genes via the Comparative Toxicogenomics Database, 1,817 key PAH-LIHC-related genes were identified. Enrichment analyses revealed associated biological pathways, and a protein–protein interaction network pinpointed 321 MCODE-derived functional module genes. A prognostic risk model based on 14 model genes was developed, demonstrating high accuracy in predicting 1 year survival for LIHC patients. Immune infiltration analysis showed distinct profiles between high- and low-risk groups. Molecular docking showed favorable docking scores and potential binding conformations of PAHs to key genes (ANXA5, LOX, HSP90AA1). Among these, the ANXA5–805-PAH complex was further subjected to a 50 ns molecular dynamics simulation to describe its short-term dynamic behavior. The results provide exploratory computational clues for PAH-related candidate targets, but further confirmation is required through rigorous docking protocol validation, repeated simulations, and experimental studies. This research provides a PAH-related prognostic model and elucidates molecular mechanisms of environmental toxin-driven liver cancer.