应用PLS-QSAR模型预测纳米金属氧化物的毒性

doi:10.3969/j.issn.1004-616x.2015.05.015

Abstract

Abstract:

OBJECTIVE: To explore the application of partial least squares-quantities structure activity relationship (PLS-QSAR) model to predict the bacterial toxicity of nanometer metal oxide, in order to provide methodological support for toxicology research. METHODS:We built 12 models through 3 ways to determine principal components and 4 ways of variables selection from published data of nanometer metal oxide (EC50) and chose the best model based on internal and external validations. RESULTS:We chose the best model obtained using forward selection of variables combining variable importance in projection(VIP) and cross validation, and CVtest principle components determination. The model had the better fitness(R²=0.974), stability (Q_CV=0.951) and prediction (Q_EXT=0.775). CONCLUSION:PLS-QSAR can be applied to predict the bacterial toxicity of nanometer metal oxide as an alternative method and it may be worthwhile to explore variable selections and determine number of principle component.

Key words: partial least squares, quantities structure activity relationship, nanometer metal oxide, toxicity

CLC Number:

R114

DENG Jingjing, WANG Meng, TANG Meng, LIU Ran, MIN Jie, YU Xiaojin. The application of PLS-QSAR model to predict the toxicity of nanometer metal oxide[J]. Carcinogenesis, Teratogenesis & Mutagenesis, 2015, 27(5): 399-403.

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The application of PLS-QSAR model to predict the toxicity of nanometer metal oxide

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