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Predicting drug-induced liver injury in human with Naïve Bayes classifier approach

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Abstract

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 81660589) and the Project for Enhancing the Research Capability of Young Teachers in Northwest Normal University (NWNU-LKQN-12-7).

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Authors and Affiliations

  1. College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People’s Republic of China

    Hui Zhang, Lan Ding, Yi Zou, Shui-Qing Hu, Hai-Guo Huang, Wei-Bao Kong & Ji Zhang

  2. State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, Sichuan, People’s Republic of China

    Hui Zhang

  3. Bioactive Products Engineering Research Center for Gansu Distinctive Plants, Northwest Normal University, Lanzhou, 730070, Gansu, People’s Republic of China

    Wei-Bao Kong & Ji Zhang

Authors
  1. Hui Zhang
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  2. Lan Ding
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  4. Shui-Qing Hu
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Correspondence to Hui Zhang.

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Zhang, H., Ding, L., Zou, Y. et al. Predicting drug-induced liver injury in human with Naïve Bayes classifier approach. J Comput Aided Mol Des 30, 889–898 (2016). https://doi.org/10.1007/s10822-016-9972-6

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  • DOI: https://doi.org/10.1007/s10822-016-9972-6

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