Predicting the cytotoxicity of disinfection by-products to Chinese hamster ovary by using linear quantitative structure-activity relationship models
Predicting the cytotoxicity of disinfection by-products to Chinese hamster ovary by using linear quantitative structure-activity relationship models
复制标题
利用线性定量构效关系模型预测消毒副产物对中国仓鼠卵巢的细胞毒性
DOI：
10.1007/s11356-019-04947-z
复制
发表时间：
2019
影响因子：
5.8
通讯作者：
Wang Dun-Qiu
中科院分区：
文献类型：
--
作者：
Qin Li-Tang;Zhang Xin;Chen Yu-Han;Mo Ling-Yun;Zeng Hong-Hu;Liang Yan-Peng;Lin Hua;Wang Dun-Qiu
需要一个合适的模型来预测当前和不断出现的消毒副产物（DBPs）的毒性。本研究旨在建立一个可靠的预测DBPs对中国仓鼠卵巢（CHO）细胞毒性的模型。以74个DBPs的CHO细胞毒性数据为终点，建立线性定量构效关系（QSAR）模型。采用多元线性回归（MLR）建立线性模型。MLR模型在内部（留一交叉验证、留多交叉验证和自举）和外部验证中均表现出较高的性能，表明其拟合优度（R2= 0.763-0.799）、稳健性（Q2 LOO = 0.718-0.745）和预测能力（CCC= 0.806-0.848）令人满意。生成的QSAR模型在训练和验证水平上显示出相当的质量。威廉姆斯图验证了模型的适用范围广，涵盖了74个结构多样的DBPs。模型中使用的分子描述符提供了影响DBP的CHO细胞毒性的可比信息。因此，线性QSAR模型可用于预测DBPs的CHO细胞毒性。
A suitable model to predict the toxicity of current and continuously emerging disinfection by-products (DBPs) is needed. This study aims to establish a reliable model for predicting the cytotoxicity of DBPs to Chinese hamster ovary (CHO) cells. We collected the CHO cytotoxicity data of 74 DBPs as the endpoint to build linear quantitative structure–activity relationship (QSAR) models. The linear models were developed by using multiple linear regression (MLR). The MLR models showed high performance in both internal (leave-one-out cross-validation, leave-many-out cross-validation, and bootstrapping) and external validation, indicating their satisfactory goodness of fit (R2= 0.763–0.799), robustness (Q2LOO= 0.718–0.745), and predictive ability (CCC= 0.806–0.848). The generated QSAR models showed comparable quality on both the training and validation levels. Williams plot verified that the obtained models had wide application domains and covered the 74 structurally diverse DBPs. The molecular descriptors used in the models provided comparable information that influences the CHO cytotoxicity of DBPs. In conclusion, the linear QSAR models can be used to predict the CHO cytotoxicity of DBPs.