title: Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.
abstract: Drug-induced eosinophilia is a potentially life-threatening adverse effect; clinical manifestations, eosinophilia-myalgia syndrome, mainly include severe skin eruption, fever, hematologic abnormalities, and organ system dysfunction. Using experimental methods to evaluate drug-induced eosinophilia is very complicated, time-consuming, and costly in the early stage of drug development. Thus, in this investigation, we established computational prediction models of drug-induced eosinophilia using SVM and naïve Bayesian approaches. For the SVM modeling, the overall prediction accuracy for the training set by means of fivefold cross-validation is 91.6 and for the external test set is 82.9 %. For the naïve Bayesian modeling, the overall prediction accuracy for the training set is 92.5 and for the external test set is 85.4 %. Moreover, some molecular descriptors and substructures considered as important for drug-induced eosinophilia were identified. Thus, we hope the prediction models of drug-induced eosinophilia built in this work should be applied to filter early-stage molecules for potential eosinophilia adverse effect, and the selected molecular descriptors and substructures of toxic compounds should be taken into consideration in the design of new candidate drugs to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China. zhanghui123gansu@163.com.|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. zhanghui123gansu@163.com.
authors.forename: Hui
authors.initials: H
authors.lastname: Zhang
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Peng
authors.initials: P
authors.lastname: Yu
authors.affiliation: 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.
authors.forename: Ming-Li
authors.initials: ML
authors.lastname: Xiang
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Xi-Bo
authors.initials: XB
authors.lastname: Li
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Wei-Bao
authors.initials: WB
authors.lastname: Kong
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Jun-Yi
authors.initials: JY
authors.lastname: Ma
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Jun-Long
authors.initials: JL
authors.lastname: Wang
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Jin-Ping
authors.initials: JP
authors.lastname: Zhang
authors.affiliation: College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.|Bioactive Products Engineering Research Center for Gansu Distinctive Plants, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
authors.forename: Ji
authors.initials: J
authors.lastname: Zhang
mesh_terms: D001499:Bayes Theorem; D004802:Eosinophilia / Q000139:chemically induced*; D006801:Humans; D004364:Pharmaceutical Preparations / Q000737:chemistry; D015203:Reproducibility of Results; D060388:Support Vector Machine
chemical_list: D004364:Pharmaceutical Preparations
keywords: Drug-induced eosinophilia; Important features; Naïve Bayesian; Prediction; Support vector machine