An integrated scheme for feature selection and parameter setting in the support vector machine modeling and its application to the prediction of pharmacokinetic properties of drugs.

OBJECTIVE: Support vector machine (SVM), a statistical learning method, has recently been evaluated in the prediction of absorption, distribution, metabolism, and excretion properties, as well as toxicity (ADMET) of new drugs. However, two problems still remain in SVM modeling, namely feature selection and parameter setting. The two problems have been shown to have an important impact on the efficiency and accuracy of SVM classification. In particular, the feature subset choice and optimal SVM parameter settings influence each other; this suggested that they should be dealt with simultaneously. In this paper, we propose an integrated scheme to account for both feature subset choice and SVM parameter settings in concert. METHOD: In the proposed scheme, a genetic algorithm (GA) is used for the feature selection and the conjugate gradient (CG) method for the parameter optimization. Several classification models of ADMET related properties have been built for assessing and testing the integrated GA-CG-SVM scheme. They include: (1) identification of P-glycoprotein substrates and nonsubstrates, (2) prediction of human intestinal absorption, (3) prediction of compounds inducing torsades de pointes, and (4) prediction of blood-brain barrier penetration. RESULTS: Compared with the results of previous SVM studies, our GA-CG-SVM approach significantly improves the overall prediction accuracy and has fewer input features. CONCLUSIONS: Our results indicate that considering feature selection and parameter optimization simultaneously, in SVM modeling, can help to develop better predictive models for the ADMET properties of drugs.

[Circadian expression of mPER1 in cultured murine myocardiocytes and effects of melatonin on it].

Objective. To investigate the mechanism of beating in cultured myocardiocytes through analyzing mPER1 expression and effect of melatonin on it. Method. Immunohistochemistry and melatonin interference test were employed. Result. mPER1 expression in cultured myocardiocytes showed circadian pattern, its acrophase was 15:20, its three consecutive daily average period length was approximately 23 h. Melatonin had little effects on its amplitude and period, but results in its phase delayed. The observation in this study was similar to those that we previously observed in cultured murine myocardiocytes beating. Conclusion. Oscillation of mPER1 gene is one of the important reasons which cause murine myocardiocytes circadian beating. Melatonin acts as "Zeitgeber" regulating mPER1 gene expression.