GGIP: Structure and sequence-based GPCR-GPCR interaction pair predictor

• Published in: Proteins, structure, function, and bioinformatics Vol. 84; no. 9; pp. 1224 - 1233
• Main Authors: Nemoto, Wataru, Yamanishi, Yoshihiro, Limviphuvadh, Vachiranee, Saito, Akira, Toh, Hiroyuki
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.09.2016; Wiley Subscription Services, Inc
• Subjects: Amino Acid Sequence; Animals; Area Under Curve; Binding Sites; computational biology; Databases, Protein; drug design; Humans; interaction partner prediction; membrane proteins; Mice; Models, Molecular; Protein Binding; Protein Interaction Domains and Motifs; Protein Multimerization; Protein Structure, Secondary; protein-protein interaction; Receptors, G-Protein-Coupled - chemistry; ROC Curve; Support Vector Machine; computational biology; protein-protein interaction; membrane proteins; support vector machine; drug design; interaction partner prediction
• ISSN: 0887-3585; 1097-0134; 1097-0134
• DOI: 10.1002/prot.25071

ABSTRACT G Protein‐Coupled Receptors (GPCRs) are important pharmaceutical targets. More than 30% of currently marketed pharmaceutical medicines target GPCRs. Numerous studies have reported that GPCRs function not only as monomers but also as homo‐ or hetero‐dimers or higher‐order molecular complexes. Many GPCRs exert a wide variety of molecular functions by forming specific combinations of GPCR subtypes. In addition, some GPCRs are reportedly associated with diseases. GPCR oligomerization is now recognized as an important event in various biological phenomena, and many researchers are investigating this subject. We have developed a support vector machine (SVM)‐based method to predict interacting pairs for GPCR oligomerization, by integrating the structure and sequence information of GPCRs. The performance of our method was evaluated by the Receiver Operating Characteristic (ROC) curve. The corresponding area under the curve was 0.938. As far as we know, this is the only prediction method for interacting pairs among GPCRs. Our method could accelerate the analyses of these interactions, and contribute to the elucidation of the global structures of the GPCR networks in membranes. Proteins 2016; 84:1224–1233. © 2016 Wiley Periodicals, Inc.