title: Fragment-based prediction of skin sensitization using recursive partitioning.
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.
authors.affiliation: 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.
authors.forename: Jing
authors.initials: J
authors.lastname: Lu
authors.forename: Mingyue
authors.initials: M
authors.lastname: Zheng
authors.forename: Yong
authors.initials: Y
authors.lastname: Wang
authors.forename: Qiancheng
authors.initials: Q
authors.lastname: Shen
authors.forename: Xiaomin
authors.initials: X
authors.lastname: Luo
authors.forename: Hualiang
authors.initials: H
authors.lastname: Jiang
authors.forename: Kaixian
authors.initials: K
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D006801:Humans; D023441:Local Lymph Node Assay; D008954:Models, Biological; D012867:Skin / Q000187:drug effects* / Q000276:immunology; D013329:Structure-Activity Relationship