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Food safety analysis: network toxicology, molecular docking, machine learning and single-cell analysis to interpret

Jingwei Li1, Hailong Yang1, Jingjia Yang2

  • 1Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Toxicology Mechanisms and Methods
|September 9, 2025
PubMed
Abstract

Insights

Sodium benzoate, a food additive, can harm kidneys. This study identified key molecular targets and pathways, like diabetic nephropathy, involved in its toxicity, with PTGS2 being a major factor.

Area of Science:

  • Toxicology
  • Molecular Biology
  • Computational Biology

Background:

  • Sodium benzoate is a widely used food additive with established safety but emerging concerns.
  • Investigating the specific mechanisms behind sodium benzoate-induced kidney damage is crucial for public health.

Purpose of the Study:

  • To elucidate the molecular mechanisms underlying sodium benzoate-induced nephrotoxicity.
  • To identify key molecular targets and biological pathways implicated in renal injury caused by sodium benzoate.

Main Methods:

  • Employed a network toxicology approach to identify critical targets and pathways.
  • Utilized molecular docking to assess binding affinities of sodium benzoate to identified targets.
  • Applied machine learning and single-cell analysis for in-depth mechanistic exploration and validation.

Main Results:

  • Protein-protein interaction network analysis pinpointed MMP2, ESR1, PARP1, PTGS2, and MAPK14 as key targets in sodium benzoate nephrotoxicity.
  • Pathway enrichment analysis identified diabetic nephropathy as a significantly affected pathway.
  • Machine learning and single-cell data confirmed Prostaglandin-endoperoxide synthase 2 (PTGS2) as a dominant contributor to the observed kidney toxicity.

Conclusions:

  • This study reveals potential molecular mechanisms of sodium benzoate-induced renal injury.
  • Findings provide a foundation for enhanced food safety assessments regarding sodium benzoate consumption.
Keywords:
Machine learningNetwork toxicologyfood additivefood safetysingle-cell analysis

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