Predicting the cytotoxicity of disinfection by-products to Chinese hamster ovary by using linear quantitative structure–activity relationship models
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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.
KeywordsDisinfection by-products Quantitative structure-activity relationship Cytotoxicity Chinese hamster ovary
Thank you for Professor Paola Gramatica (University of Insubria) for providing the QSARINS software (website www.qsar.it).
This work was supported by Provincial Natural Science Foundation of Guangxi (2017GXNSFAA198346), the National Natural Science Foundation of China (21866010, 21667013, and 51638006), Special Funding for Guangxi ‘BaGui Scholar’ Construction Projects, and Guangxi Science and Technology Planning Project (GuiKe-AD18126018).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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