Seo Myungwon, Chae Chong Hak, Lee Yuno, Kim Ha Ryong, Kim Jongwoon
Chemical Safety Research Center, Korea Research Institute of Chemical Technology, Daejeon 34114, Korea.
Data Convergence Drug Research Center, Korea Research Institute of Chemical Technology, Daejeon 34114, Korea.
Toxics. 2021 Mar 16;9(3):59. doi: 10.3390/toxics9030059.
The adverse outcome pathway (AOP) was introduced as an alternative method to avoid unnecessary animal tests. Under the AOP framework, an in silico methods, molecular initiating event (MIE) modeling is used based on the ligand-receptor interaction. Recently, the intersecting AOPs (AOP 347), including two MIEs, namely peroxisome proliferator-activated receptor-gamma (PPAR-γ) and toll-like receptor 4 (TLR4), associated with pulmonary fibrosis was proposed. Based on the AOP 347, this study developed two novel quantitative structure-activity relationship (QSAR) models for the two MIEs. The prediction performances of different MIE modeling methods (e.g., molecular dynamics, pharmacophore model, and QSAR) were compared and validated with in vitro test data. Results showed that the QSAR method had high accuracy compared with other modeling methods, and the QSAR method is suitable for the MIE modeling in the AOP 347. Therefore, the two QSAR models based on the AOP 347 can be powerful models to screen biocidal mixture related to pulmonary fibrosis.
不良结局途径（AOP）作为一种避免不必要动物试验的替代方法被引入。在AOP框架下，一种基于配体-受体相互作用的计算机方法——分子起始事件（MIE）建模被采用。最近，提出了包括两个MIE（即过氧化物酶体增殖物激活受体γ（PPAR-γ）和Toll样受体4（TLR4））的交叉AOP（AOP 347），其与肺纤维化相关。基于AOP 347，本研究针对这两个MIE开发了两个新的定量构效关系（QSAR）模型。不同MIE建模方法（如分子动力学、药效团模型和QSAR）的预测性能与体外试验数据进行了比较和验证。结果表明，与其他建模方法相比，QSAR方法具有较高的准确性，且QSAR方法适用于AOP 347中的MIE建模。因此，基于AOP 347的这两个QSAR模型可成为筛选与肺纤维化相关的杀生物混合物的有力模型。
