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Computational Analysis of the 3-D structure of Human GPR87 Protein: Implications for Structure-Based Drug Design

  • Rani, Mukta (Department of Pharmacology and Therapeutics, King George’s Medical University, (Erstwhile C.S.M. Medical University)) ;
  • Nischal, Anuradha (Department of Pharmacology and Therapeutics, King George’s Medical University, (Erstwhile C.S.M. Medical University)) ;
  • Sahoo, Ganesh Chandra (Biomedical Informatics Centre, Rajendra Memorial Research Institute of Medical Sciences) ;
  • Khattri, Sanjay (Department of Pharmacology and Therapeutics, King George’s Medical University, (Erstwhile C.S.M. Medical University))
  • Published : 2013.12.31

Abstract

The G-protein coupled receptor 87 (GPR87) is a recently discovered orphan GPCR which means that the search of their endogenous ligands has been a novel challenge. GPR87 has been shown to be overexpressed in squamous cell carcinomas (SCCs) or adenocarcinomas in lungs and bladder. The 3D structure of GPR87 was here modeled using two templates (2VT4 and 2ZIY) by a threading method. Functional assignment of GPR87 by SVM revealed that along with transporter activity, various novel functions were predicted. The 3D structure was further validated by comparison with structural features of the templates through Verify-3D, ProSA and ERRAT for determining correct stereochemical parameters. The resulting model was evaluated by Ramachandran plot and good 3D structure compatibility was evidenced by DOPE score. Molecular dynamics simulation and solvation of protein were studied through explicit spherical boundaries with a harmonic restraint membrane water system. A DRY-motif (Asp-Arg-Tyr sequence) was found at the end of transmembrane helix3, where GPCR binds and thus activation of signals is transduced. In a search for better inhibitors of GPR87, in silico modification of some substrate ligands was carried out to form polar interactions with Arg115 and Lys296. Thus, this study provides early insights into the structure of a major drug target for SCCs.

Keywords

References

  1. Altschul SF, Gish W, Miller W, et al (1990). Basic local alignment search tool. J Mol Biol, 215, 403-10. https://doi.org/10.1016/S0022-2836(05)80360-2
  2. Arnold K, Bordoli L, Kopp J, et al (2006). The swiss-model workspace: a web-based environment for protein structure homology modeling. Bioinformatics, 22, 195-201. https://doi.org/10.1093/bioinformatics/bti770
  3. Audet M, Bouvier M (2012). Restructuring G-protein-coupled receptor activation. Cell, 151, 14-23. https://doi.org/10.1016/j.cell.2012.09.003
  4. Bokoch MP, Zou Y, Rasmussen SG, et al (2010). Ligand-specific regulation of the extracellular surface of a G-protein-coupled receptor. Nature, 463, 108-12. https://doi.org/10.1038/nature08650
  5. Brooks BR, Bruccoleri RE, Olafson BD, et al (1993). CHARMM: a program for macromolecular energy minimization and dynamics calculations. J Comput Chem, 4, 187-217.
  6. Cai CZ, Han LY, Ji ZL, et al (2003). SVM-Prot: web-based support vector machine software for functional classification of a protein from its primary sequence. Nucleic Acids Res, 31, 3692-7. https://doi.org/10.1093/nar/gkg600
  7. Chung S, Funakoshi T, Civelli O (2008). Orphan GPCR research. Brit J Pharmacol, 153, 339-46.
  8. Claros MG, von Heijne G (1994). TopPred II:An improved software for membrane protein structure predictions. Comput Appl Biosci, 10, 685-6.
  9. Colovos C, Yeates TO (1993). Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci, 2, 1511-9. https://doi.org/10.1002/pro.5560020916
  10. Combet C, Jambon M, Deleage G, et al (2002). Geno3D: An automated protein modeling Web server. Bioinformatics, 18, 213-4. https://doi.org/10.1093/bioinformatics/18.1.213
  11. Costanzi S (2012). Homology modeling of class a G proteincoupled receptors. Methods Mol Biol, 857, 259-79.
  12. Cserzo M, Wallin E, Simon I, et al (1994). Prediction of transmembrane alpha-helices in prokaryotic membrane proteins: Application of the Dense Alignment Surface (DAS) method. J Mol Biol, 243, 388-96. https://doi.org/10.1006/jmbi.1994.1666
  13. Das S, Rani M, Pandey K, et al (2012). Combination of paromomycin and miltefosine promotes TLR4-dependent induction of antileishmanial immune response in vitro. J Antimicrob Chemother, 67, 2373-8. https://doi.org/10.1093/jac/dks220
  14. Dereeper A, Guignon V, Blanc G, et al (2008). Phylogeny.fr: robust phylogenetic analysis for the non-specialist. Nucleic Acids Res, 36, 465-9. https://doi.org/10.1093/nar/gkn180
  15. Dundas J, Ouyang Z, Tseng J, et al (2006). CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acid Res, 34, 116-8.
  16. Glatt S, Halbauer D, Heindl S (2008). hGPR87 contributes to viability of human tumor cells. Int J Cancer, 122, 2008-16. https://doi.org/10.1002/ijc.23349
  17. Gugger M, White R, Song S (2008). GPR87 is an over expressed G-protein coupled receptor in squamous cell carcinoma of the lung. Dis Markers, 24, 41-50. https://doi.org/10.1155/2008/857474
  18. Hans BO, Petrine W, Anders AJ (2007). Structure, pharmacology and therapeutic prospects of family C G-protein coupled receptors. Current Drug Targets, 8, 169-84. https://doi.org/10.2174/138945007779315614
  19. Hendlich M, Rippmann F, Barnickel G (1997). LIGSITE: automatic and efficient detection of potential small moleculebinding sites in proteins. J Mol Graph Model, 15, 359-63. https://doi.org/10.1016/S1093-3263(98)00002-3
  20. Hirokawa T, Boon-Chieng S, Mitaku S (1998). SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics, 14, 378-9. https://doi.org/10.1093/bioinformatics/14.4.378
  21. Hofmann K, Stoffel W (1993). TMbase: a database of membrane spanning proteins segments. Biol Chem Hoppe-Seyler, 374, 166-70.
  22. Holm L, Kaariainen S, Rosenstrom P, et al (2008). Searching protein structure databases with DaliLitev.3. Bioinformatics, 24, 2780-1. https://doi.org/10.1093/bioinformatics/btn507
  23. Jones DT, Taylor WR, Thornton JM (1994). A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry, 33, 3038-49. https://doi.org/10.1021/bi00176a037
  24. Juretic D, Zoranic L, Zucic D (2002). Basic charge clusters and predictions of membrane protein topology. J Chem Inf Comput Sci, 42, 620-32. https://doi.org/10.1021/ci010263s
  25. Kcrley-Haniilton JS, Pike, AM, Li N, et al (2005). A p53-do mutant transcriptional response to cisplalin in testicular germ cell tumor-derived human embyomnal carcinoma. Oncoxene, 24, 6090-100.
  26. Kelley LA, Sternberg MJ (2009). Protein structure prediction on the Web: a case study using the Phyre server. Nat Protoc, 4, 363-71. https://doi.org/10.1038/nprot.2009.2
  27. Krogh A, Larsson B, von Heijne G, et al (2001). Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol, 305, 567-80 https://doi.org/10.1006/jmbi.2000.4315
  28. Kyeong MK, Marc GC (2008). Complementary roles of the DRY motif and C-terminus tail of GPCRS for G protein coupling and $\beta$-arrestin interaction. Biochem Bioph Res Comm, 366, 42-7. https://doi.org/10.1016/j.bbrc.2007.11.055
  29. Lambert N, Leonard X, De Bolle, ED (2002). ESyPred3D: prediction of proteins 3D structures. Bioinformatics, 18, 1250-6. https://doi.org/10.1093/bioinformatics/18.9.1250
  30. Larkin MA, Blackshields G, Brown NP, et al (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23, 2947-8. https://doi.org/10.1093/bioinformatics/btm404
  31. Laskowski RA, MacArthur MW, Moss DS, et al (1993).PROCHECK: a program to check the stereochemical qualityof protein structures. J Appl Cryst, 26, 283-91. https://doi.org/10.1107/S0021889892009944
  32. Mobarec JC, Sanchez R, Filizola M (2009). Modern homology modeling of G-protein coupled receptors: which structural template to use? J Med Chem, 52, 5207-16. https://doi.org/10.1021/jm9005252
  33. Nonaka Y, Hiramoto H, Fujita N (2005). Identification of endogenous surrogate ligands for human $P2Y_{12}$ receptors by in silico and in vitro methods. Biochem Biophys Res Commun, 337, 281-8. https://doi.org/10.1016/j.bbrc.2005.09.052
  34. Ochiai S, Furuta D, Sugita K, et al (2013). GPR87 mediates lysophosphatidic acid-induced colony dispersal in A431 cells. Eur J Pharmacol, 715, 15-20. https://doi.org/10.1016/j.ejphar.2013.06.029
  35. Ota T, Suzuki Y, Nishikawa T, et al (2004). Complete sequencing and characterization of 21,243 full-length human cDNAs. Nat Genet, 36, 40-5. https://doi.org/10.1038/ng1285
  36. Pandian S, Shylajanaciyar MD, Murugesan R (2011). Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking. J Mol Model, 17, 1565-77. https://doi.org/10.1007/s00894-010-0860-z
  37. Rani M, Dikhit MR, Sahoo GC, et al (2011) Comparative domain modeling of human EGF-like module EMR2 and study of interaction of the fourth domain of EGF with chondroitin 4-sulphate. J Biomedical Res, 25, 100-10. https://doi.org/10.1016/S1674-8301(11)60013-4
  38. Rasmussen SG, Choi HJ, Rosenbaum DM, et al (2007). Crystal structure of the human beta2 adrenergic G-protein-coupled receptor. Nature, 15, 383-7.
  39. Robert TD, Silvio JG (2007). G-protein-coupled receptors and cancer. Nature Publishing Group, 7, 79-94.
  40. Roderick EH (2006). 3D Structure and the Drug Discovery Process. RSC Publishing group, 13, 9780854043514.
  41. Rost B, Yachdav G, Liu J (2004). The predict protein server. Nucleic Acids Research, 32, 321-6. https://doi.org/10.1093/nar/gkh377
  42. Ryckaert JP, Ciccotti G, Berendsen HJC (1977). Numerical integration of the cartesian equations of motion of a system with constraints; molecular dynamics of n-alkanes. J Comp Phys, 23, 327-41. https://doi.org/10.1016/0021-9991(77)90098-5
  43. Sadiq SK, Guixa-Gonzalez R, Dainese E, et al (2013). Molecular modeling and simulation of membrane lipid-mediated effects on GPCRs. Curr Med Chem, 20, 22-38.
  44. Sahoo GC, Dikhit MR, Rani M, et al (2013). Analysis of sequence, structure of GAPDH of Leishmania donovani and its interactions. J Biomol Struct Dyn, 31, 258-75. https://doi.org/10.1080/07391102.2012.698189
  45. Shailza S, Sharma DK (2011). In silico modeling in conjunction with natural products: paving the way for rational drugdesign. Biotechnology and Molecular Biology Review, 6, 88-93.
  46. Shen MY, Sali A (2006). Statistical potential for assessment and prediction of protein structures. Protein Science, 15, 2507-24. https://doi.org/10.1110/ps.062416606
  47. Shimamura T, Hiraki K, Takahashi N, et al (2008). Crystal structure of squid rhodopsin with intracellularly extended cytoplasmic region. J Biol Chem, 283, 17753-6. https://doi.org/10.1074/jbc.C800040200
  48. Tusnady GE, Simon I (1998). Principles governing amino acid composition of integral membrane proteins - application to topology prediction. J Mol Biol, 283, 489-506. https://doi.org/10.1006/jmbi.1998.2107
  49. Varsha G (2008). Metallo beta lactamases in Pseudomonas aeruginosa and Acinetobacter species. Expert Opin Invest Drugs, 17, 131-43. https://doi.org/10.1517/13543784.17.2.131
  50. Venkatachalam CM, Jiang X, Oldfield T et al (2003). LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. J Mol Graphics, 21, 289-307. https://doi.org/10.1016/S1093-3263(02)00164-X
  51. Warne A, Serrano-Vega MJ, Baker JG, et al (2008). Structure of the Beta1-adrenergic G Protein-Coupled Receptor. Nature, 454, 454-86.
  52. Wiederstein M, Sippl MJ (2007). ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research, 35, 407-10.
  53. Wittenberger T, Schaller HC, Hellebrand S (2001). An expressed sequence tag (EST) data mining strategy succeeding in the discovery of new G-protein coupled receptors. J Mol Biol, 307, 799-813. https://doi.org/10.1006/jmbi.2001.4520
  54. Zhang Y (2008). I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, 9, 40. https://doi.org/10.1186/1471-2105-9-40