ArticleNutrients2026
Computational Prediction of Hesperetin Modulatory Targets in Dibutyl Phthalate-Associated Steatotic Liver Injury: An Integrated Network Toxicology, Molecular Docking, and AOP-Based Study.
Article in Nutrients, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND/
objectivesDibutyl phthalate (DBP) is a ubiquitous environmental plasticizer that has been associated with metabolic dysfunction and steatotic liver injury. Hesperetin, a citrus flavonoid, has reported hepatoprotective properties, but its potential protective mechanisms against DBP-associated steatotic liver injury remain incompletely characterized.
methodsThis study integrated network toxicology, network pharmacology, protein-protein interaction analysis, Gene Ontology and KEGG enrichment, molecular docking with redocking validation, sensitivity analysis, and an adverse outcome pathway (AOP) framework to systematically explore the predictive networks linking DBP exposure, MASLD (historically termed NAFLD)-related targets, and hesperetin intervention.
resultsThe DBP-MASLD network identified TP53, PPARG, TNF, AKT1, and CASP3 as candidate hub targets associated with toxicity, whereas the hesperetin-MASLD network highlighted HSP90AA1, PPARG, ESR1, TNF, and MDM2 as candidate modulatory targets. Integrated pathway analysis indicated that these targets converged mainly on the lipid and atherosclerosis pathway (hsa05417). Triplicate molecular docking, AUC-ROC differentiation validation, and PLIP analysis suggested that Hesperetin (and its glucuronide metabolite) may competitively interact with the exact same active pockets as DBP (and its MBP metabolite). These computational predictions suggest a structural basis for potential interaction, but do not confirm physiological competitive displacement.
conclusionsThis in silico study identifies PPARG and TNF as candidate hub targets, providing a structural hypothesis for hesperetin's potential modulatory effects on DBP-induced steatotic liver injury. These computational predictions establish a theoretical dual-network framework that warrants subsequent in vitro and in vivo experimental validation.
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