{"title":"Computational toxicology prioritization of CYP3A4 and DPP7 as candidate triclosan-relevant molecular targets in ulcerative colitis.","authors":"Jiafeng Wang, Songsong Jiang, Yingying Zhang, Hao Gao, Xiaoqi Zhao, Lixiang Liu, Zijian Li","doi":"10.1080/15376516.2026.2698865","DOIUrl":null,"url":null,"abstract":"<p><p>Triclosan (TCS), a synthetic broad-spectrum antimicrobial and novel persistent organic pollutant, is detected in over 75% of human urine samples, yet its molecular targets in ulcerative colitis (UC) remain unclear. We integrated network toxicology, multi-cohort machine learning, molecular docking, 100-ns all-atom molecular dynamics (MD) simulation, and single-cell transcriptomics to address this gap.Intersecting UC differentially expressed genes with database-derived TCS targets yielded 479 shared candidate targets; because these databases include indirect and probabilistic associations,this set was treated as hypothesis-generating. KEGG enrichment identified the AGE-RAGE signaling pathway, PPAR signaling, and TNF signaling among the top enriched pathways. LASSO regression and random forest algorithms distilled a 10-gene diagnostic signature that achieved cross-cohort AUC of 0.910-1.000 across six independent GEO datasets, consistent with strong discriminative performance.Molecular docking predicted Vina scores of -7.1 kcal/mol (CYP3A4) and -7.0 kcal/mol (DPP7);redocking and decoy analyses supported protocol specificity but not biochemical binding or inhibition. Over 100 ns of MD simulation, the docked poses remained stable for both targets. Single-cell RNA sequencing GSE214695 independently corroborated cell-type-specific CYP3A4 downregulation in epithelial cells and broad DPP7 upregulation across immune subsets in UC.CellOracle-based in silico perturbation predicted that CYP3A4 suppression would impair cytoplasmic translation, while DPP7 suppression would polarize innate inflammation toward an IL-1β-driven phenotype. Together, these analyses computationally prioritize CYP3A4 and DPP7 as candidate TCS-relevant targets in UC and generate testable hypotheses for future experimental validation; they do not by themselves establish direct target engagement, inhibition, or causal contribution to UC.</p>","PeriodicalId":23177,"journal":{"name":"Toxicology Mechanisms and Methods","volume":" ","pages":"1-14"},"PeriodicalIF":2.7000,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicology Mechanisms and Methods","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15376516.2026.2698865","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 0
Abstract
Triclosan (TCS), a synthetic broad-spectrum antimicrobial and novel persistent organic pollutant, is detected in over 75% of human urine samples, yet its molecular targets in ulcerative colitis (UC) remain unclear. We integrated network toxicology, multi-cohort machine learning, molecular docking, 100-ns all-atom molecular dynamics (MD) simulation, and single-cell transcriptomics to address this gap.Intersecting UC differentially expressed genes with database-derived TCS targets yielded 479 shared candidate targets; because these databases include indirect and probabilistic associations,this set was treated as hypothesis-generating. KEGG enrichment identified the AGE-RAGE signaling pathway, PPAR signaling, and TNF signaling among the top enriched pathways. LASSO regression and random forest algorithms distilled a 10-gene diagnostic signature that achieved cross-cohort AUC of 0.910-1.000 across six independent GEO datasets, consistent with strong discriminative performance.Molecular docking predicted Vina scores of -7.1 kcal/mol (CYP3A4) and -7.0 kcal/mol (DPP7);redocking and decoy analyses supported protocol specificity but not biochemical binding or inhibition. Over 100 ns of MD simulation, the docked poses remained stable for both targets. Single-cell RNA sequencing GSE214695 independently corroborated cell-type-specific CYP3A4 downregulation in epithelial cells and broad DPP7 upregulation across immune subsets in UC.CellOracle-based in silico perturbation predicted that CYP3A4 suppression would impair cytoplasmic translation, while DPP7 suppression would polarize innate inflammation toward an IL-1β-driven phenotype. Together, these analyses computationally prioritize CYP3A4 and DPP7 as candidate TCS-relevant targets in UC and generate testable hypotheses for future experimental validation; they do not by themselves establish direct target engagement, inhibition, or causal contribution to UC.
期刊介绍:
Toxicology Mechanisms and Methods is a peer-reviewed journal whose aim is twofold. Firstly, the journal contains original research on subjects dealing with the mechanisms by which foreign chemicals cause toxic tissue injury. Chemical substances of interest include industrial compounds, environmental pollutants, hazardous wastes, drugs, pesticides, and chemical warfare agents. The scope of the journal spans from molecular and cellular mechanisms of action to the consideration of mechanistic evidence in establishing regulatory policy.
Secondly, the journal addresses aspects of the development, validation, and application of new and existing laboratory methods, techniques, and equipment.