Integrating Network Toxicology, Machine Learning, and Molecular Dynamics to Explore the Molecular Network of Triclosan-Induced Acute Myocardial Infarction

Qi Zhang, Siwei Zou, Ziyao Yang, Jingbo Cao, Yajuan Fu, Chenjie Feng, Yue Sun, Anning Yang

Triclosan (TCS) exposure is linked to increased acute myocardial infarction (AMI) risk, but underlying mechanisms remain unclear. Here, we integrated network toxicology, machine learning, molecular simulations, and in vitro assays to delineate this pathway. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) identified 37 candidate genes, which were refined via machine learning to 8 core regulators (including PTGS2). Molecular docking and molecular dynamics (MD) simulations confirmed high-affinity, stable binding of TCS to PTGS2. In cardiomyocytes, TCS upregulated PTGS2 and the injury marker cTnI, an effect reversed by the PTGS2 inhibitor celecoxib. These findings establish PTGS2 as a critical mediator of TCS-induced cardiomyocyte injury, providing a potential therapeutic target for TCS-associated cardiovascular damage.