Classification of GPCRs using family specific motifs

Abstract

The classification of G-Protein Coupled Receptor (GPCR) sequences is an important problem that arises from the need to close the gap between the large number of orphan receptors and the relatively small number of annotated receptors. Equally important is the characterization of GPCR Class A subfamilies and gaining insight into the ligand interaction since GPCR Class A encompasses a very large number of drug-targeted receptors. In this thesis, a method for Class A subfamily classification using sequence-derived motifs which characterizes the subfamilies by discovering receptor-ligand interaction sites is proposed. The motifs that best characterize a subfamily are selected by the proposed Distinguishing Power Evaluation (DPE) technique. The experiments performed on GPCR sequence databases show that the proposed method outperforms state-of-the-art classification techniques for GPCR Class A subfamily prediction. An important contribution of this thesis is to discover key receptor-ligand interaction sites which is very important for drug design.