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Exploring the structure of opioid receptors with homology modeling based on single and multiple templates and subsequent docking: A comparative study

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Abstract

Opioid receptors are the principal targets for opioids, which have been used as analgesics for centuries. Opioid receptors belong to the rhodopsin family of G-protein coupled receptors (GPCRs). In the absence of crystal structures of opioid receptors, 3D homology models have been reported with bovine rhodopsin as a template, though the sequence homology is low. Recently, it has been reported that use of multiple templates results in a better model for a target having low sequence identity with a single template. With the objective of carrying out a comparative study on the structural quality of the 3D models based on single and multiple templates, the homology models for opioid receptors (mu, delta and kappa) were generated using bovine rhodopsin as single template and the recently deposited crystal structures of squid rhodopsin, turkey β-1 and human β-2 adrenoreceptors along with bovine rhodopsin as multiple templates. In this paper we report the results of comparison between the refined 3D models based on multiple sequence alignment (MSA) and models built with bovine rhodopsin as template, using validation programs PROCHECK, PROSA, Verify 3D, Molprobity and docking studies. The results indicate that homology models of mu and kappa with multiple templates are better than those built with only bovine rhodopsin as template, whereas, in many aspects, the homology model of delta opioid receptor with single template is better with respect to the model based on multiple templates. Three nonselective ligands were docked to both the models of mu, delta and kappa opioid receptors using GOLD 3.1. The results of docking complied well with the pharamacophore, reported for nonspecific opioid ligands. The comparison of docking results for models with multiple templates and those with single template have been discussed in detail. Three selective ligands for each receptor were also docked. As the crystallographic structures are not yet known, this comparison will help in choosing better homology models of opioid receptors for studying ligand receptor interactions to design new potent opioid antagonists.

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References

  1. Simonds WF (1988) The molecular basis of opioid receptor function. Endocrine Rev 9:1214–1216. doi:10.1210/edrv-9-2-200

    Article  Google Scholar 

  2. Chaturvedi K, Christoffers KH, Singh K, Howells RD (2000) Structure and regulation of opioid receptors. Biopolymers 55:334–346. doi:10.1002/1097-0282

    Article  CAS  Google Scholar 

  3. Habib-Nezhad B, Hanifian M, Mahmoudian M (1996) Computer-aided receptor modeling of human opioid receptors: ( Mu, Kappa and Delta). J Mol Model 2:362–369. doi:10.1007/s0089460020362

    Article  Google Scholar 

  4. Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA (2000) Crystal structure of rhodopsin: A G protein-coupled receptor. Science 289:739–745. doi:10.1126/science.289.5480.739

    Article  CAS  Google Scholar 

  5. Strahs D, Weintein H (1997) Comparative modeling and molecular dynamics studies of the delta, kappa and mu opioid receptors. Protein Eng 10:1019–1038

    Article  CAS  Google Scholar 

  6. Aburi M, Smith PE (2004) Modeling and simulation of the human delta opioid receptor. Protein Sci 13:1997–2008. doi:10.1110/ps.04673404

    Article  CAS  Google Scholar 

  7. Zhang T, Sham YY, Rajamani R, Gao J, Portoghese PS (2005) Homology modeling and molecular dynamics simulations of the mu opioid receptor in a membrane-aqueous system. Chem Bio Chem 6:853–859. doi:10.1002/cbic.200400207

    CAS  Google Scholar 

  8. Whisstock JC, Lesk AM (2003) Prediction of protein function from protein sequence and structure. Q Rev Biophys 36:307–340. doi:10.1017/S0033583503003901

    Article  CAS  Google Scholar 

  9. Murakami M, Kouyama T (2008) Crystal structure of squid rhodopsin. Nature 453:363–367. doi:10.1038/nature06925

    Article  CAS  Google Scholar 

  10. Warne A, Serrano-Vega MJ, Baker JG, Moukhametzianov R, Edwards PC, Henderson R, Leslie AGW, Tate CG, Schertler GFX (2008) Structure of the Beta1-Adrenergic G Protein-Coupled Receptor. Nature 454:486. doi:10.1038/nature07101

    Article  CAS  Google Scholar 

  11. Rasmussen SG, Choi HJ, Rosenbaum DM, Kobilka TS, Thian FS, Edwards PC, Burghammer M, Ratnala VR, Sanishvili R, Fischetti RF, Schertler GF, Weis WI, Kobilka BK (2007) Crystal structure of the human beta2 adrenergic G-protein-coupled receptor. Nature 450:383–387. doi:10.1038/nature06325

    Article  CAS  Google Scholar 

  12. Mobarec JC, Sanchez R, Filizola M (2009) Modern Homology Modeling of G-Protein Coupled Receptors: Which Structural Template to Use? J Med Chem 52(16):5207–5216. doi:10.1021/jm9005252

    Article  CAS  Google Scholar 

  13. Filizola M, Villar HO, Loew GH (2001) Molecular determinants of nonspecific recognition of delta, mu and kappa opioid receptors. Biorg Med Chem 9:69–76. doi:10.1016/S0968-0896(00)00223-6

    Article  CAS  Google Scholar 

  14. Insight II (2000) Homology User Guide. Accelrys Inc, San Diego

    Google Scholar 

  15. Hyperchem 7.5, Hypercube, Inc,Gainesville, FL

  16. Cerius2, Version 4.6, Accelrys Inc, San Diego, CA, USA

  17. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267(3):727–748. doi:10.1006/jmbi.1996.0897

    Article  CAS  Google Scholar 

  18. www.pymol.org

  19. www.rcsb.org

  20. Laskowski RA, MacArthur MW, Moss D, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Cryst 26:283–291. doi:10.1107/S0021889892009944

    Article  CAS  Google Scholar 

  21. Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics 22:195–201. doi:10.1093/bioinformatics/bti770

    Article  CAS  Google Scholar 

  22. Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410. doi:10.1093/nar/gkm290

    Article  Google Scholar 

  23. Sippl MJ (1993) Recognition of Errors in Three-Dimensional Structures of Proteins. Proteins 17:355–362

    Article  CAS  Google Scholar 

  24. Chen VB, Arendall WB, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, Murray LW, Richardson JS, Richardson DC (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr 66:12–21. doi:10.1107/S0907444909042073

    Article  Google Scholar 

  25. http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_seccons.html

  26. Kabsch W, Sander C (1983) Dictionary of protein secondary structure: Pattern recognition of hydrogen bonded and geometrical features. Biopolymers 22:2577–2637

    Article  CAS  Google Scholar 

  27. Eisenberg D, Luthy R, Bowie JU (1997) VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol 277:396–404

    Article  CAS  Google Scholar 

  28. Befort K, Tabbara L, Bausch S, Chavkin C, Evans C, Kieffer B (1996) The conserved aspartate residue in the third putative transmembrane domain of the delta-opioid receptor is not the anionic counterpart for cationic opiate binding but is a constituent of the receptor binding site. Mol Pharmacol 49(2):216–223

    CAS  Google Scholar 

  29. Befort K, Tabbara L, Kling D, Maigret B, Kieffer BL (1996) Role of aromatic transmembrane residues of the delta-opioid receptor in ligand recognition. J Biol Chem 271(17):10161–10168. doi:10.1074/jbc.271.17.10161

    Article  CAS  Google Scholar 

  30. Ananthan S, Kezar HS, Carter RL, Saini SK, Rice KC, Wells JL, Davis P, Xu H, Dersch CM, Bilsky EJ, Porreca F, Rothman RB (1999) Synthesis, Opioid Receptor Binding, and Biological Activities of Naltrexone-Derived Pyrido- and Pyrimidomorphinans. J Med Chem 42(3527):3538

    Google Scholar 

  31. Goldstein A, Naidu A (1989) Multiple opioid receptors:ligand selectivity profiles and binding site signatures. Mol Pharmacol 36:265–272

    CAS  Google Scholar 

  32. Su TP (1984) Further demonstration of kappa binding sites in the brain:evidence of heterogeneity. J Pharmacol Exp Ther 232(1):144–148

    Google Scholar 

  33. Spetea M, Schullner F, Moisa RC, Berzetei-Gurske IP, Schraml B, Dorfler C, Aceto MD, Harris LS, Coop A, Schmidhammer H (2004) Synthesis and Biological Evaluation of 14-Alkoxymorphinans. 21.1 Novel 4-Alkoxy and 14-Phenylpropoxy Derivatives of the mu Opioid Receptor Antagonist Cyprodime. J Med Chem 47:3242–3247. doi:10.1021/jm031126k

    Article  CAS  Google Scholar 

  34. Black SL, Chauvignac C, Grundt P, Miller CN, Wood S, Traynor JR, Lewis JW, Husbands SM (2003) Guanidino N-Substituted and N, N-Disubstituted Derivatives of the κ-Opioid antagonist GNTI. J Med Chem 46(25):5505–5511. doi:10.1021/jm0309203

    Article  CAS  Google Scholar 

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Acknowledgments

The authors thank Council for Scientific and Industrial Research (CSIR), New Delhi, for providing financial grant for the project NPIF-109/119. IB thanks CSIR for project assistantship. Authors thank Mitul Bhattacharya of Department of Electronics Accreditation for Computer Courses (DOEACC) Kolkata Center for assistance in literature survey.

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  1. Structural Biology and Bioinformatics Division, (A unit of CSIR), Indian Institute of Chemical Biology, Kolkata, 700032, India

    Indrani Bera, Aparna Laskar & Nanda Ghoshal

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  1. Indrani Bera
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  2. Aparna Laskar
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  3. Nanda Ghoshal
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Correspondence to Nanda Ghoshal.

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Bera, I., Laskar, A. & Ghoshal, N. Exploring the structure of opioid receptors with homology modeling based on single and multiple templates and subsequent docking: A comparative study. J Mol Model 17, 1207–1221 (2011). https://doi.org/10.1007/s00894-010-0803-8

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