Citation: Nasser Goudarzi, Mohammad Goodarzi, M. Arab Chamjangali, M. H. Fatemi. Application of a new SPA-SVM coupling method for QSPR study of electrophoretic mobilities of some organic and inorganic compounds[J]. Chinese Chemical Letters, ;2013, 24(10): 904-908. shu

Application of a new SPA-SVM coupling method for QSPR study of electrophoretic mobilities of some organic and inorganic compounds

a Faculty of Chemistry, Shahrood University of Technology, P.
a Faculty of Chemistry, Shahrood University of Technology, P.O. Box 316, Shahrood, Iran;
2.
b Department of Chemistry, Faculty of Sciences, Yong Researchers Club, Azad University, Arak, Iran;
3.
c Faculty of Chemistry, Mazandaran University, Babolsar, Iran

Corresponding author: Nasser Goudarzi,
Received Date: 11 March 2013
Available Online: 28 May 2013

In this work, two chemometrics methods are applied for the modeling and prediction of electrophoretic mobilities of some organic and inorganic compounds. The successive projection algorithm, feature selection (SPA) strategy, is used as the descriptor selection and model development method. Then, the support vector machine (SVM) and multiple linear regression (MLR) model are utilized to construct the non-linear and linear quantitative structure-property relationship models. The results obtained using the SVM model are compared with those obtained using MLR reveal that the SVM model is of much better predictive value than the MLR one. The root-mean-square errors for the training set and the test set for the SVM model were 0.1911 and 0.2569, respectively, while by the MLR model, they were 0.4908 and 0.6494, respectively. The results show that the SVM model drastically enhances the ability of prediction in QSPR studies and is superior to the MLR model.
- Quantitative structure-mobility,
- relationship,
- Support vector machine,
- Electrophoretic mobility,
- Successive projection algorithm,
- Multiple linear regression
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