Abstract Acetyl triethyl citrate (ATEC), a phthalate-free plasticizer widely used in industry, is considered safer than di(2-ethylhexyl) phthalate (DEHP), yet its long-term nephrotoxicity in chronic kidney disease (CKD) is poorly understood. Here, we applied an integrated workflow combining network toxicology, machine learning, molecular docking, and molecular dynamics simulations to evaluate CKD risk from ATEC exposure. PubChem/ProTox-3.0 screening identified 43 differentially expressed genes (DEGs) linking ATEC and CKD. Protein–protein interaction analysis, along with Gene Ontology and KEGG enrichment, indicated that these DEGs are involved in signal transduction, metabolism, and immune regulation. Analysis of GEO dataset GSE104954 using five machine learning algorithms pinpointed two candidate key genes, ALB and F11. Molecular docking (CB-DOCK2) and dynamics simulations (GROMACS) suggested stable binding conformations between ATEC and both proteins under simulated conditions. This “risk identification–gene screening–functional analysis–mechanism exploration” framework provides molecular-level insights into the potential nephrotoxic effects of ATEC and uncovers plausible pathological links between ATEC exposure and CKD progression, offering new insights into the safety evaluation of emerging plasticizers.
Yang et al. (Mon,) studied this question.