The Mechanism of Bisphenol S‐Induced Atherosclerosis Elucidated Based on Network Toxicology, Molecular Docking, and Machine Learning

对接(动物) 机制(生物学) 化学 计算生物学 双酚A 药理学 毒理 医学 生物 有机化学 物理 护理部 量子力学 环氧树脂
作者
Bing Guo,He Xuan
出处
期刊:Journal of Applied Toxicology [Wiley]
被引量:2
标识
DOI:10.1002/jat.4768
摘要

The increasing prevalence of environmental pollutants has raised public concern about their potential role in diseases such as atherosclerosis (AS). Existing studies suggest that chemicals, including bisphenol S (BPS), may adversely affect cardiovascular health, but the specific mechanisms remain unclear. This study aims to elucidate the effects of BPS on AS and the underlying mechanisms. Through an extensive search of databases such as ChEMBL, STITCH, SwissTargetPrediction, SuperPred, SEA, and GEO, we identified 34 potential targets related to BPS-induced AS. A target network was constructed using the STRING platform and Cytoscape software. GO and KEGG functional enrichment analysis using the DAVID database revealed that BPS may promote the occurrence of AS by interfering with critical biological processes such as glutathione metabolism, nitrogen metabolism, and tyrosine metabolism. This was followed by the selection of 4 core targets-aminopeptidase n (ANPEP), alcohol dehydrogenase 5 (ADH5), lysosomal pro-x carboxypeptidase (PRCP), and microsomal glutathione s-transferase 1 (MGST1)-using five machine learning methods. These core targets play a pivotal role in BPS-induced AS. Furthermore, molecular docking confirmed the tight binding between BPS and these core targets. In conclusion, this study provides a theoretical framework for understanding the molecular mechanisms of BPS-induced AS and contributes scientific evidence for the development of prevention and treatment strategies for cardiovascular diseases triggered by BPS exposure.
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