ArticleBMC nephrology2025
Deconvolution of molecular mechanisms in di-n-butyl phthalate/mono-n-butyl phthalate induced diabetic kidney disease by integrated machine learning and molecular docking.
Article in BMC nephrology, 2025. 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
backgroundThis study investigates the molecular mechanisms by which di-n-butyl phthalate (DBP) and mono-n-butyl phthalate (MnBP)-induced diabetic kidney disease (DKD).
methodsDifferential 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.
resultsSix 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.
conclusionThis 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.
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