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