Deconvolution of molecular mechanisms in di-n-butyl phthalate/mono-n-butyl phthalate induced diabetic kidney disease by integrated machine learning and molecular docking

Background This study investigates the molecular mechanisms by which di-n-butyl phthalate (DBP) and mono-n-butyl phthalate (MnBP)-induced diabetic kidney disease (DKD). Methods Differential expression analysis and Weighted Gene Co-expression Network Analysis were used to identify DKD-associated targets. Machine learning, molecular docking, molecular dynamics simulations, and public databases were integrated to explore the interaction between DBP/MnBP and target proteins. Results Six core genes were identified: DUSP1 , PTGS2 , FOSB , GDF15 , NR4A1 , and CXCR2 . Among these, DUSP1 and FOSB showed excellent performance in single-gene ROC curves, box plots, public databases, and molecular docking. Molecular docking and molecular dynamics simulations demonstrated a stable binding affinity between DBP/MnBP and the target proteins. Conclusion This research suggests that DBP/MnBP may promote DKD by targeting these six core genes. The binding capacity and stability of DBP/MnBP with these genes were confirmed by machine learning, molecular docking, and molecular dynamics simulations. These findings provide a direction for future in-depth research on the DBP/MnBP-induced DKD mechanism.