Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

A modeling strategy for G-protein coupled receptors

Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Fahrstr. 17, 91054 Erlangen, Germany

Topical Section: Membrane protein structural biology

Cell responses can be triggered via G-protein coupled receptors (GPCRs) that interact with small molecules, peptides or proteins and transmit the signal over the membrane via structural changes to activate intracellular pathways. GPCRs are characterized by a rather low sequence similarity and exhibit structural differences even for functionally closely related GPCRs. An accurate structure prediction for GPCRs is therefore not straightforward. We propose a computational approach that relies on the generation of several independent models based on different template structures, which are subsequently refined by molecular dynamics simulations. A comparison of their conformational stability and the agreement with GPCR-typical structural features is then used to select a favorable model. This strategy was applied to predict the structure of the herpesviral chemokine receptor US28 by generating three independent models based on the known structures of the chemokine receptors CXCR1, CXCR4, and CCR5. Model refinement and evaluation suggested that the model based on CCR5 exhibits the most favorable structural properties. In particular, the GPCR-typical structural features, such as a conserved water cluster or conserved non-covalent contacts, are present to a larger extent in the model based on CCR5 compared to the other models. A final model validation based on the recently published US28 crystal structure confirms that the CCR5-based model is the most accurate and exhibits 80.8% correctly modeled residues within the transmembrane helices. The structural agreement between the selected model and the crystal structure suggests that our modeling strategy may also be more generally applicable to other GPCRs of unknown structure.
  Figure/Table
  Supplementary
  Article Metrics

References

1. Takata K, Matsuzaki T, Tajika Y (2004) Aquaporins: water channel proteins of the cell membrane. Prog Histochem Cytochem 39: 1–83.    

2. Nagel G, Szellas T, Huhn W, et al. (2003) Channelrhodopsin-2, a directly light-gated cation-selective membrane channel. Proc Natl Acad Sci U S A 100: 13940–13945.    

3. Lai EC (2004) Notch signaling: control of cell communication and cell fate. Development 131: 965–973.    

4. Jacoby E, Bouhelal R, Gerspacher M, et al. (2006) The 7 TM G-Protein-Coupled Receptor Target Family. ChemMedChem 1: 760–782.    

5. Gentry PR, Sexton PM, Christopoulos A (2015) Novel Allosteric Modulators of G Protein-coupled Receptors. J Biol Chem 290: 19478–19488.    

6. Strotmann R, Schröck K, Böselt I, et al. (2011) Evolution of GPCR: Change and continuity. Mol Cell Endocrinol 331: 170–178.    

7. Ferré S (2015) The GPCR heterotetramer: challenging classical pharmacology. Trends Pharmacol Sci 36: 145–152.    

8. Joost P, Methner A (2002) Phylogenetic analysis of 277 human G-protein-coupled receptors as a tool for the prediction of orphan receptor ligands. Genome Biology 3: research0063.1–research0063.16.

9. Kledal TN, Rosenkilde MM, Schwartz TW (1998) Selective recognition of the membrane-bound CX3C chemokine, fractalkine, by the human cytomegalovirus-encoded broad-spectrum receptor US28. FEBS Letters 441: 209–214.    

10. Tan Q, Zhu Y, Li J, et al. (2013) Structure of the CCR5 Chemokine Receptor-HIV Entry Inhibitor Maraviroc Complex. Science 341: 1387–1390.    

11. Sali A, Blundell TL (1993) Comparative Protein Modelling by Satisfaction of Spatial Restraints. J Mol Biol 234: 779–815.    

12. Wu B, Chien EYT, Mol CD, et al. (2010) Structures of the CXCR4 Chemokine GPCR with Small-Molecule and Cyclic Peptide Antagonists. Science 330: 1066–1071.    

13. Park SH, Das BB, Casagrande F, et al. (2012) Structure of the chemokine receptor CXCR1 in phospholipid bilayers. Nature 491: 779–783.

14. Burg JS, Ingram JR, Venkatakrishnan AJ, et al. (2015) Structural basis for chemokine recognition and activation of a viral G protein-coupled receptor. Science 347: 1113–1117.    

15. Bateman A, Birney E, Durbin R, et al. (2000) The Pfam Protein Families Database.

16. Eddy SR (2009) A new Generation of Homology Search Tools based on Probabilistic Inference. Genome Inform 23: 205–211.

17. Johnson LS, Eddy S, Portugaly E (2010) Hidden Markov model speed heuristic and iterative HMM search procedure. BMC Bioinformatics 11: 431.    

18. Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol 7: e1002195.    

19. Hooft RWW, Vriend G, Sander C, et al. (1996) Errors in protein structures. Nature 381: 272.

20. Dolinsky TJ, Nielsen JE, McCammon JA, et al. (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res 32: W665–W667.    

21. Berendsen HJC, Postma JPM, van Gunsteren WF, et al. (1981) Interaction models for water in relation to protein hydration. Intermolecular Forces 14: 331–342.    

22. Siu SWI, Vácha R, Jungwirth P, et al. (2008) Biomolecular simulations of membranes: Physical properties from different force fields. J Chem Phys 128: 125103.    

23. Schrödinger LLC (2010) The PyMOL Molecular Graphics System, Version 1.3r1.

24. Berendsen HJC, van der Spoel D, van Drunen R (1995) GROMACS: A message-passing parallel molecular dynamics implementation. Comput Phys Commun 91: 43–56.    

25. Lindahl E, Hess B, van der Spoel D (2001) GROMACS 3.0: a package for molecular simulation and trajectory analysis. J Mol Model 7: 306–317.

26. van der Spoel D, Lindahl E, Hess B, et al. (2005) GROMACS: Fast, flexible, and free. J Comput Chem 26: 1701–1718.    

27. Hess B, Kutzner C, van der Spoel D, et al. (2008) GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J Chem Theory Comput 4: 435–447.    

28. Pronk S, Páll S, Schulz R, et al. (2013) GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29: 845–854.

29. Humphrey W, Dalke A, Schulten K (1996) VMD: Visual molecular dynamics. J Mol Graph 14: 33–38.    

30. Hornak V, Abel R, Okur A, et al. (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins 65: 712–725.    

31. Cornell WD, Cieplak P, Bayly CI, et al. (1995) A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules. J Am Chem Soc: 5179–5197.

32. Darden T, York D, Pedersen L (1993) Particle mesh Ewald: An N ⋅ log(N) method for Ewald sums in large systems. J Chem Phys 98: 10089–10092.    

33. Hess B, Bekker H, Berendsen HJC, et al. (1997) LINCS: A linear constraint solver for molecular simulations. J Comput Chem 18: 1463–1472.

34. Wang J, Wolf RM, Caldwell JW, et al. (2004) Development and testing of a general amber force field. J Comput Chem 25: 1157–1174.    

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

36. Holm L, Sander C (1992) Evaluation of protein models by atomic solvation preference. J Mol Biol 225: 93–105.    

37. Wallace AC, Laskowski RA, Thornton JM (1995) LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng 8: 127–134.    

38. Laskowski RA, Swindells MB (2011) LigPlot+: Multiple Ligand-Protein Interaction Diagrams for Drug Discovery. J Chem Inf Model 51: 2778–2786.    

39. Buck DK, Collins AA (2004) POV-Ray – The Persistence of Vision Raytracer.

40. Ballesteros JA, Weinstein H (1995) Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Method Neurosci 25: 366–428.    

41. Apweiler R, Bairoch A, Wu CH, et al. (2004) UniProt: the Universal Protein Knowledgebase. Nucleic Acids Res 32: 115–119.    

42. Feng Z, Alqarni MH, Yang P, et al. (2014) Modeling, molecular dynamics simulation, and mutation validation for structure of cannabinoid receptor 2 based on known crystal structures of GPCRs. J Chem Inf Model 54: 2483–2499.    

43. Kralj A, Kurt E, Tschammer N, et al. (2014) Synthesis and Biological Evaluation of Biphenyl Amides That Modulate the US28 Receptor. ChemMedChem 9: 151–168.    

44. Rodriguez D, Gutiérrez-de-Terán H (2012) Characterization of the homodimerization interface and functional hotspots of the CXCR4 chemokine receptor. Proteins 80: 1919–1928.

45. Dror RO, Arlow DH, Maragakis P, et al. (2011) Activation mechanism of the beta2-adrenergic receptor. Proc Natl Acad Sci U S A 108: 18684–18689.    

46. Rosenbaum DM, Zhang C, Lyons JA, et al. (2011) Structure and function of an irreversible agonist-beta2 adrenoceptor complex. Nature 469: 236–240.    

47. Deupi X, Kobilka B (2007) Activation of G Protein-Coupled Receptors. Mechanisms and Pathways of Heterotrimeric G Protein Signaling. Academic Press, 137–166.

48. Lodowski DT, Angel TE, Palczewski K (2009) Comparative Analysis of GPCR Crystal Structures. Photochem Photobiol 85: 425–430.    

49. Venkatakrishnan AJ, Deupi X, Lebon G, et al. (2013) Molecular signatures of G-protein-coupled receptors. Nature 494: 185–194.    

50. Tehan BG, Bortolato A, Blaney FE, et al. (2014) Unifying family A GPCR theories of activation. Pharmacol Ther 143: 51–60.    

51. Yohannan S, Faham S, Yang D, et al. (2004) The evolution of transmembrane helix kinks and the structural diversity of G protein-coupled receptors. Proc Natl Acad Sci U S A 101: 959–963.    

52. Angel TE, Chance MR, Palczewski K (2009) Conserved waters mediate structural and functional activation of family A (rhodopsin-like) G protein-coupled receptors. Proc Natl Acad Sci U S A 106: 8555–8560.    

53. Angel TE, Gupta S, Jastrzebska B, et al. (2009) Structural waters define a functional channel mediating activation of the GPCR, rhodopsin. Proc Natl Acad Sci U S A 106: 14367–14372.    

54. Piirainen H, Ashok Y, Nanekar RT, et al. (2011) Structural features of adenosine receptors: From crystal to function. Biochim Biophys Acta - Biomembranes 1808: 1233–1244.    

Copyright Info: © 2016, Heinrich Sticht, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline
Copyright © AIMS Press All Rights Reserved