Revealing 1,3-diphenylpropane’s coagulation toxicity via infomaxnet-based network toxicology and molecular simulations
Yan Pan, Hongxia Cai, Yufeng Ran, Hexiang Qiu, Zhihang Huang, Dan Wu, Wenjing Zhang, Nan Zhang, Lei Cheng, Juan Long, Shan Gao, Xiaowei Qiu, Guojun Li, Bo Xian · Ecotoxicology and Environmental Safety · 2025
The pervasive use of plastic products has led to environmental contamination by compounds like 1,3-diphenylpropane (SD-1), a polystyrene dimer found in plastic food containers that poses potential health risks. SD-1 can induce coagulation disorder, however, the toxic mechanisms of SD-1 has not been elucidated yet. This study proposes a network toxicology analysis framework-InfomaxNet, which successfully addresses the challenge of lacking prior biological knowledge by analyzing complex biological networks using only network topology. Using the deep learning model MolTrans to predict SD-1 targets, InfomaxNet identified the critical proteins AKT2 and F9. Molecular dynamics simulations revealed that the binding of SD-1 to F9 (FIXa) induces conformational anomalies in its active site, disrupting protein function and increasing the risk of coagulation disorders. In vitro experiments confirmed that SD-1 interferes with coagulation pathways involving F9. Subsequently, acute toxicity experiments in Caenorhabditis elegans and RT-qPCR validated the impact of SD-1 on AKT2 and its downstream signaling pathways. This study introduces the InfomaxNet framework and applies it to network toxicology analysis, combining deep learning and molecular dynamics simulations to uncover the toxic mechanisms of SD-1 on the coagulation system by pinpointing the peptidase domain of F9, providing new insights for toxicological studies of novel pollutants.