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G-protein coupled receptors (GPCRs) constitute a broad class of cell-surfacereceptors in eukaryotes and they possess seven transmembrane a-helical domains.GPCRs are usually classified into several functionally distinct families thatplay a key role in cellular signalling and regulation of basic physiologicalprocesses. We can develop statistical models based on these common featuresthat can be used to classify proteins, to predict new members, and to study thesequence-function relationship of this protein function group. In this study,SVM based classification model has been developed for the identification ofhuman gpcr sequences. Sequences of Level 1 subfamilies of Class A rhodopsin isconsidered as case study. In the present study, an attempt has been made toclassify GPCRs on the basis of species. The present study classifies human gpcrsequences with rest of the species available in GPCRDB. Classification is basedon specific information derived from the n-terminal and extracellular loops ofthe sequences, some physicochemical properties and amino acid composition ofcorresponding gpcr sequences. Our method classifies Level 1 subfamilies ofGPCRs with 94% accuracy.

SVM Model for Identification of human GPCRs