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Exploring toxicity of perfluorinated compounds through complex network and pathway modeling.

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Perfluorinated compounds (PFCs) disrupt human hormone balance and health by affecting protein and gene networks. Branched PFCs show weaker protein binding than linear PFCs, influencing disease correlations.

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Area of Science:

  • Environmental Toxicology
  • Molecular Biology
  • Computational Chemistry

Background:

  • Perfluorinated compounds (PFCs) pose significant human health risks by interfering with cellular signaling pathways and hormone balance.
  • PFCs interact with multiple proteins, suggesting complex toxicological effects beyond single-target modifications.

Purpose of the Study:

  • To construct a PFC-target interaction network to understand the systemic effects of PFCs.
  • To investigate the differences in network characteristics between branched and linear PFCs.
  • To identify key target genes and their correlation with PFC-induced diseases.

Main Methods:

  • Construction of a PFC-target interaction network.
  • Molecular dynamics (MD) simulations to assess binding affinities.
  • Network analysis to identify central node genes.

Main Results:

  • Significant differences observed in complex network characteristics between branched and linear PFCs.
  • Molecular dynamics simulations revealed weaker binding of branched PFCs to target proteins compared to linear PFCs.
  • Four central node genes were identified, showing correlations with diseases such as obesity, hepatocellular carcinoma, and diabetes.

Conclusions:

  • PFC toxicity arises from disturbances in complex protein or gene networks, not just single targets.
  • The structural differences between branched and linear PFCs influence their network interactions and toxicological profiles.
  • The identified key genes highlight potential pathways linking PFC exposure to major human diseases.