Lab for Bone Metabolism, Xi'an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China; Toxicology Research Center, Institute for Hygiene of Ordnance Industry, Xi'an, Shaanxi 710065, China.
Lab for Bone Metabolism, Xi'an Key Laboratory of Special Medicine and Health Engineering, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China.
Ecotoxicol Environ Saf. 2022 Sep 1;242:113839. doi: 10.1016/j.ecoenv.2022.113839. Epub 2022 Jul 9.
1,2,4-triazole derivatives exhibit various biological activities, including antibacterial and antifungal properties. On the other hand, these chemicals may have unique cumulative and harmful effects on living organisms. The goal of this work is to use quantitative structure-toxicity relationship (QSTR) and interspecies quantitative toxicity-toxicity relationship (iQSTTR) models to predict the acute toxicity of 1,2,4-triazole derivatives. The QSTR models were generated by multiple linear regression (MLR) following the OECD recommendations for QSAR model development and validation. The iQSTTR models were constructed using data on acute oral toxicity in rats and mice, as well as the 2D descriptor. The application domain (AD) analysis was used to identify model outliers and determine if the forecast was credible. Six QSTR models were successfully constructed in rats and mice using various delivery methods, and the scatter plots demonstrated excellent consistency across training and test sets. According to external and internal validation criteria, all six QSTR models may be broadly accepted; however, the orally administered mice model was the optimum one among the six species. Several chemicals with leverage values above the requirements were identified as response or structural outliers in the training sets for six QSTR and two iQSTTR models. All outliers, however, fell slightly outside the threshold or had low prediction errors, which may have had little impact on the capacity to forecast and were therefore preserved in the final models. In fact, neither the QSTR nor the iQSTTR test sets contained any response outliers. Additionally, all external and internal validation results for the iQSTTR models were approved, with the iQSTTR models outperforming the comparable QSTR models, which are deemed more dependable. The QSTR and iQSTTR models performed well in predicting toxicity using test sets, which would be beneficial in evaluating and synthesizing newly discovered 1,2,4-triazoles derivatives with low toxicity and environmental hazard.
1,2,4-三唑衍生物具有多种生物活性,包括抗菌和抗真菌特性。另一方面,这些化学物质可能对生物体具有独特的累积和有害影响。本工作的目的是利用定量构效关系(QSAR)和种间定量毒性关系(iQSTR)模型来预测 1,2,4-三唑衍生物的急性毒性。QSAR 模型是根据 OECD 推荐的 QSAR 模型开发和验证建议,通过多元线性回归(MLR)生成的。iQSTR 模型是使用大鼠和小鼠急性口服毒性数据以及二维描述符构建的。应用域(AD)分析用于识别模型异常值并确定预测是否可信。使用不同的给药方法在大鼠和小鼠中成功构建了六个 QSTR 模型,散点图显示了训练集和测试集之间的极好一致性。根据外部和内部验证标准,所有六个 QSTR 模型都可以广泛接受;然而,在六种物种中,经口给予的小鼠模型是最佳的。在六个 QSTR 和两个 iQSTR 模型的训练集中,有几个具有杠杆值超过要求的化学物质被确定为响应或结构异常值。然而,所有异常值都略低于阈值或预测误差较低,这可能对预测能力影响不大,因此保留在最终模型中。事实上,无论是 QSTR 还是 iQSTR 测试集都没有包含任何响应异常值。此外,iQSTR 模型的所有外部和内部验证结果都得到了批准,iQSTR 模型的表现优于可比的 QSTR 模型,被认为更可靠。QSAR 和 iQSTR 模型在使用测试集预测毒性方面表现良好,这将有助于评估和合成具有低毒性和环境危害的新发现的 1,2,4-三唑衍生物。