Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China; Department of Medical Technology, Beijing Pharmaceutical University of Staff and Workers (CPC Party School of Beijing Tong Ren Tang (Group) co., Ltd.), Beijing 100079, China.
J Hazard Mater. 2024 Dec 5;480:136071. doi: 10.1016/j.jhazmat.2024.136071. Epub 2024 Oct 6.
Per- and polyfluoroalkyl substances (PFASs) are widely used in modern industry, causing many adverse effects on both the environment and human health. In this study, for the first time, we followed OECD guidelines to systematically investigate the quantitative structure-activity relationship (QSAR) of the oral acute toxicity of PFASs to Rat and Mouse using simple 2D descriptors. The Read-Across similarity descriptors and 2D descriptors were also combined to develop the quantitative read-across structure-activity relationship (q-RASAR) models. Interspecies toxicity (iST) correlation was also explored between the two rodent species. All developed QSAR, q-RASAR and iST models met the state-of-the-art validation criteria and were applied for toxicity predictions of hundreds of untested PFASs in true external sets. Subsequently, we performed the priority ranking of the untested PFASs based on the model predictions, with the mechanistic interpretation of the top 20 most toxic PFASs predicted by both QSAR and q-RASAR models. The two univariate iST models were also used for filling the interspecies toxicity data gap. Overall, the developed QSAR, q-RASAR and iST models can be used as effective tools for predicting the oral acute toxicity of untested PFASs to Rat and Mouse, thus being important for risk assessment of PFASs in ecological environment.
全氟和多氟烷基物质(PFASs)广泛应用于现代工业,对环境和人类健康造成许多不良影响。在这项研究中,我们首次按照经合组织(OECD)指南,使用简单的 2D 描述符,系统地研究了 PFASs 对大鼠和小鼠口服急性毒性的定量构效关系(QSAR)。还将 Read-Across 相似性描述符和 2D 描述符结合起来,开发了定量 Read-Across 结构-活性关系(q-RASAR)模型。同时还探索了两种啮齿动物之间的种间毒性(iST)相关性。所有开发的 QSAR、q-RASAR 和 iST 模型都满足了最先进的验证标准,并应用于数百种未经测试的 PFASs 在真实外部集的毒性预测。随后,我们根据模型预测对未经测试的 PFASs 进行了优先级排序,并对 QSAR 和 q-RASAR 模型预测的前 20 种毒性最大的 PFASs 进行了机制解释。还使用了两种单变量 iST 模型来填补种间毒性数据缺口。总体而言,开发的 QSAR、q-RASAR 和 iST 模型可作为预测未测试的 PFASs 对大鼠和小鼠口服急性毒性的有效工具,从而对生态环境中 PFASs 的风险评估具有重要意义。