Prediction of GPCR-G Protein Coupling Specificity Using Features of Sequences and Biological Functions

Understanding the coupling specificity between G protein-coupled receptors(GPCRs) and specific classes of G proteins is important for further elucidationof receptor functions within a cell. Increasing information on GPCR sequencesand the G protein family would facilitate prediction of the coupling properties ofGPCRs. In this study, we describe a novel approach for predicting the couplingspecificity between GPCRs and G proteins. This method uses not only GPCRsequences but also the functional knowledge generated by natural language pro-cessing, and can achieve 92.2% prediction accuracy by using the C4.5 algorithm.Furthermore, rules related to GPCR-G protein coupling are generated. The com-bination of sequence analysis and text mining improves the prediction accuracy forGPCR-G protein coupling specificity, and also provides clues for understandingGPCR signaling.