Integrating machine learning and molecular docking to elucidate the mechanism of atrial fibrillation induced by di(2-ethylhexyl) phthalate.

ABSTRACT: Environmental exposure is closely associated with the development of cardiovascular diseases. This study aims to explore the molecular mechanism by which Di (2-ethylhexyl) phthalate (DEHP) induces atrial fibrillation (AF). AF-related target genes were identified through differential expression analysis of multiple datasets. Machine learning algorithms, Weighted Gene Co-expression Network Analysis (WGCNA), Machine learning (ML) and molecular docking technology were integrated to investigate the binding interaction between DEHP and target proteins. A total of 8 potential key targets (ITGB2, ARPC1B, RYR2, FPR2, MPEG1, PRKCD, LCP1, RAC2) involved in DEHP-induced AF were identified. ML analysis confirmed these genes as core regulatory genes, among which ITGB2, ARPC1B, and RYR2 exhibited high di

SUBMITTER: Shi W 

PROVIDER: S-EPMC12808640 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature