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http://dx.doi.org/10.1007/s10059-009-0091-2

A Machine Learning Based Method for the Prediction of G Protein-Coupled Receptor-Binding PDZ Domain Proteins  

Eo, Hae-Seok (School of Biological Sciences, Seoul National University)
Kim, Sungmin (Interdisciplinary Program in Bioinformatics, Seoul National University)
Koo, Hyeyoung (Department of Biological Science, Sangji University)
Kim, Won (School of Biological Sciences, Seoul National University)
Publication Information
Molecules and Cells / v.27, no.6, 2009 , pp. 629-634 More about this Journal
Abstract
G protein-coupled receptors (GPCRs) are part of multi-protein networks called 'receptosomes'. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.
Keywords
G protein-coupled receptor; GPCR interacting protein; machine learning; PDZ domain; support vector machine;
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1 Basdevant, N., Weinstein, H., and Ceruso, M. (2006). Thermodynamic basis for promiscuity and selectivity in protein-protein interactions: PDZ domains, a case study. J. Am. Chem. Soc. 128, 12766-12777   DOI   ScienceOn
2 Boeckmann, B., Bairoch, A., Apweiler, R., Blatter, M.C., Estreicher, A., Gasteiger, E., Martin, M.J., Michoud, K., O'Donovan, C., Phan, I., et al. (2003). The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res. 31, 365-370   DOI   ScienceOn
3 Chi, C.N., Engstr$\ddot{o}$m, $\AA$., Gianni, S., Larsson, M., and Jemth, P. (2006). Two conserved residues govern the salt and pH dependencies of the binding reaction of a PDZ domain. J. Biol. Chem. 281, 36811-36818   DOI   ScienceOn
4 Ferraro, E., Via, A., Ausiello, G., and Helmer-Citterich, M. (2006). A novel structure-based encoding for machine-learning applied to the inference of SH3 domain specificity. Bioinformatics 22, 2333-2339   DOI   ScienceOn
5 Hanyaloglu, A.C., and von Zastrow, M. (2008). Regulation of GPCRs by endocytic membrane trafficking and its potential implications. Annu. Rev. Pharmacol. Toxicol. 48, 537-568   DOI   ScienceOn
6 Kreienkamp, H.J. (2002). Organisation of G-protein-coupled receptor signaling complexes by scaffolding proteins. Curr. . 2, 504-514
7 Kurakin, A., Swistowski, A., Wu, S.C., and Bredesen, D.E. (2007). The PDZ domain as a complex adaptive system. PLoS ONE 2, e953   DOI   PUBMED
8 Nourry, C., Grant, S.G., and Borg, J.P. (2003). PDZ domain proteins: Plug and play!. Sci. STK. 179, RE7
9 Reina, J., Lacroix, E., Hobson, S.D., Fernandez-Ballester, G., Rybin, V., Schwab, M.S., Serrano, L., and Gonzalez, C. (2002). Computer- aided design of a PDZ domain to recognize new target sequences. Nat. Struct. Biol. 9, 621-627
10 Beuming, T., Skrabanek, L., Niv, M.Y., Mukherjee, P., and Weinstein, H. (2005). PDZBase: a protein-protein interaction database for PDZ-domains. Bioinformatics 21, 827-828   DOI   ScienceOn
11 Hung, A.Y., and Sheng, M. (2002). PDZ domains: Structural modules for protein complex assembly. J. Biol. Chem. 277, 5699-5702   DOI   ScienceOn
12 Joachims, T. (1999). Making large-scale SVM learning practical. Advances in kernel methods-support vector machines (MITPress)
13 Fang, M., Tao, Y.X., He, F., Zhang, M., Levine, C.F., Mao, P., Tao, F., Chou, C.L., Sadegh-Nasseri, S., and Johns, R.A. (2003). Synaptic PDZ domain-mediated protein interactions are disrupted by inhalational anesthetics. J. Biol. Chem. 278, 36669-36675   DOI   ScienceOn
14 Songyang, Z., Fanning, A.S., Fu, C., Xu, J., Marfatia, S.M., Chishti, A.H., Crompton, A., Chan, A.C., Anderson, J.M., and Cantley, L.C. (1997). Recognition of unique carboxyl-terminal motifs by distinct PDZ domains. Science 275, 73-77   DOI   PUBMED   ScienceOn
15 Mathivanan, S., Periaswamy, B., Gandhi, T.K., Kandasamy, K., Suresh, S., Mohmood, R., Ramachandra, Y.L., and Pandey, A. (2006). An evaluation of human protein-protein interaction data in the public domain. BMC Bioinformatics 7, S19   PUBMED
16 Skelton, N.J., Koehler, M.F., Zobel, K., Wong, W.L., Yeh, S., Pisabarro, M.T., Yin, J.P., Lasky, L.A., and Sidhu, S.S. (2003). Origins of PDZ domain ligand specificity. J. Biol. Chem. 278, 7645-7654   DOI   ScienceOn
17 Stiffler, M.A., Chen, J.R., Grantcharova, V.P., Lei, Y., Fuchs, D., Allen, J.E., Zaslavskaia, L.A., and MacBeath, G. (2007). PDZ domain binding selectivity is optimized across the mouse proteome. Science 317, 364-369   DOI   PUBMED   ScienceOn
18 Day, P., and Kobilka, B. (2006). PDZ-domain arrays for identifying components of GPCR signaling complexes. Trends Pharmacol. Sci. 27, 509-511   DOI   ScienceOn
19 Eo, H.S., Choi, J.P., Noh, S.J., Hur C.G., and Kim, W. (2007). A combined approach for the classification of G protein-coupled receptors and its application to detect GPCR splice variants. Comput. Biol. Chem. 31, 246-256   DOI   ScienceOn
20 Vaccaro, P., and Dente, L. (2002). PDZ domains: troubles in classification. FEBS Lett. 512, 345-349   DOI   PUBMED   ScienceOn
21 Zhang, L., Shao, C., Zheng, D., and Gao, Y. (2006). An integrated machine learning system to computationally screen protein databases for protein binding peptide ligands. Mol. Cell. Proteomics 5, 1224-1232   DOI   ScienceOn
22 Bockaert, J., Roussignol, G., B$\acute{e}$camel, C., Gavarini, S., Joubert, L., Dumuis, A., Fagni, L., and Marin, P. (2004). GPCR-interacting proteins (GIPs): nature and functions. Biochem. Soc. Trans. 32, 851-855   DOI   ScienceOn
23 van Ham, M., and Hendriks, W. (2003). PDZ domains-glue and guide. Mol. Biol. Rep. 30, 69-82   DOI   ScienceOn
24 Doyle, D.A., Lee, A., Lewis, J., Kim, E., Sheng, M., and Mackinnon, R. (1996). Crystal structures of a complexed and peptide-free membrane protein-binding domain: molecular basis of peptide recognition by PDZ. Cell 85, 1067-1076   DOI   ScienceOn
25 Altuvia, Y., and Margalit, H. (2004). A structure-based approach for prediction of MHC-binding peptides. Methods 34, 454-459   DOI   ScienceOn
26 Wiedemann, U., Boisguerin, P., Leben, R., Leitner, D., Krause, G., Moelling, K., Volkmer-Engert, R., and Oschkinat, H. (2004). Quantification of PDZ domain specificity, prediction of ligand affinity and rational design of super-binding peptides. J. Mol. Biol. 343, 703-718   DOI   ScienceOn
27 Grantham, R. (1974). Amino acid difference formula to help explain protein evolution. Science 185, 862-864   DOI   PUBMED   ScienceOn
28 Bezprozvanny, I., and Maximov, A. (2001). Classification of PDZ domains. FEBS Lett. 509, 457-462   DOI   ScienceOn
29 Giallourakis, C., Cao, Z., Green, T., Wachtel, H., Xie, X., Lopez- Illasaca, M., Daly, M., Rioux, J., and Xavier, R. (2006). A molecular-properties-based approach to understanding PDZ domain proteins and PDZ ligands. Genome Res. 16, 1056-1072   DOI   ScienceOn