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Fragment-based prediction of skin sensitization using recursive partitioning

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Abstract

Skin sensitization is an important toxic endpoint in the risk assessment of chemicals. In this paper, structure–activity relationships analysis was performed on the skin sensitization potential of 357 compounds with local lymph node assay data. Structural fragments were extracted by GASTON (GrAph/Sequence/Tree extractiON) from the training set. Eight fragments with accuracy significantly higher than 0.73 (p < 0.1) were retained to make up an indicator descriptor fragment. The fragment descriptor and eight other physicochemical descriptors closely related to the endpoint were calculated to construct the recursive partitioning tree (RP tree) for classification. The balanced accuracy of the training set, test set I, and test set II in the leave-one-out model were 0.846, 0.800, and 0.809, respectively. The results highlight that fragment-based RP tree is a preferable method for identifying skin sensitizers. Moreover, the selected fragments provide useful structural information for exploring sensitization mechanisms, and RP tree creates a graphic tree to identify the most important properties associated with skin sensitization. They can provide some guidance for designing of drugs with lower sensitization level.

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Acknowledgments

This work was supported by Hi-TECH Research and Development Program of China (Grant 2006AA020402), National S&T Major Project (Grants 2009ZX09301-001, 2009ZX09501-001), and the State Key Program of Basic Research of China (Grant 2009CB918502).

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Authors and Affiliations

  1. Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China

    Jing Lu, Mingyue Zheng, Yong Wang, Qiancheng Shen, Xiaomin Luo, Hualiang Jiang & Kaixian Chen

  2. School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China

    Hualiang Jiang

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  1. Jing Lu
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  2. Mingyue Zheng
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  5. Xiaomin Luo
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Correspondence to Xiaomin Luo or Hualiang Jiang.

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Lu, J., Zheng, M., Wang, Y. et al. Fragment-based prediction of skin sensitization using recursive partitioning. J Comput Aided Mol Des 25, 885–893 (2011). https://doi.org/10.1007/s10822-011-9472-7

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