G-protein coupled receptors (GPCRs) represent one of the most important classesof drug targets for pharmaceutical industry and play important roles in cellularsignal transduction. Predicting the coupling specificity of GPCRs to G-proteins isvital for further understanding the mechanism of signal transduction and the func-tion of the receptors within a cell, which can provide new clues for pharmaceuticalresearch and development. In this study, the features of amino acid compositionsand physiochemical properties of the full-length GPCR sequences have been ana-lyzed and extracted. Based on these features, classifiers have been developed topredict the coupling specificity of GPCRs to G-proteins using support vector ma-chines. The testing results show that this method could obtain better predictionaccuracy.
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