Poster Presentation 2014 International Biophysics Congress

GGIP: GPCR-GPCR interaction pair predictor (#466)

Wataru Nemoto 1 , Yashihiro Yamanishi 2 , Vachiranee Limviphuvadh 3 , Hiroyuki Toh 4
  1. Division of Life Science and Engineering, Tokyo Denki University (TDU), Hiki-gun, Saitama, Japan
  2. Medical Institute of Bioregulation (MiB), Kyushu University, Fukuoka, Japan
  3. Bioinformatics Institute (BII), A*STAR Singapore, Singapore
  4. Computational Biology Research Center (CBRC), Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan

G-Protein Coupled Receptors (GPCRs) are important pharmaceutical targets. More than 30% of currently marketed pharmaceutical medicines target GPCRs. A number of studies have reported that GPCRs function not only as their monomers but also as homo- or hetero-dimers or higher-order molecular complexes. Many GPCRs exert a wide variety of functions by a specific combination of GPCR subtypes. In addition, some GPCRs are reported to be associated with diseases. Thus, GPCR oligomerization is now recognized as an important event in various biological phenomena, and many researchers are investigating the subject. As of today, more than 100 GPCR subtype pairs have been reported to form homo- or hetero-oligomers, and the number is still increasing. However, there are more GPCR pairs whose oligomer formations have not been examined yet. Hence, we have developed a method to predict interacting pairs for GPCR oligomerization by integrating structure and sequence information. The performance of our method was evaluated by Receiver Operating Characteristic curve. The corresponding Area Under the Curve (AUC) was 0.889. As far as we know, there is no method to predict interacting pairs among GPCRs. We will show examples of predicted GPCR pairs, which may be associated with diseases through disease tissue specific upregulation of GPCR genes or nsSNPs on GPCR genes corresponding to the interfaces for GPCR oligomerization.