1. 1

2. A project of David Lutje Hulsik and Tim Hulsen May 7th, 2001 2

3. What are GPCRs? Membrane-bound receptors A very large number of different domains both to bind their ligand and to activate G proteins. 6 different families Transducing messages as photons, organic odorants, nucleotides, nucleosides, peptides, lipids and proteins. 3

4. Seven transmembrane regions GPCR Structure Conserved residues and motifs (i.e. NPXXY) Hydrophobic/ hydrophilic domains 4

5. GPCR-G protein coupling Agonist binding to receptor becomes stronger upon G protein coupling GDP is released G protein takes up GTP G protein binds to activated receptor GTP uptake triggers release of G protein from receptor Receptor gets activated by agonist 5

6. Research goals To determine whether predictions made about the structure of GPCRs are correct To see which methods give the best results 6

7. Residue numbering:Schwartz / Baldwin (e.g. V.16) Ballesteros-Weinstein (e.g. 6.50) etc. Major research difficulties Bacteriorhodopsin as template Available high-resolution structural information 7

8. Bacteriorhodopsin Photosynthetic bacteria Conformation Helical arrangement G proteins not involved Proton pumping 8

9. Studies on GPCRs Mutation studies Photoaffinity Protease studies Cystein scanning NMR Spinlabel 9

10. Methods Collecting data Structure validation with WHAT-IF Making alignment with the use of several articles which compare a GPCR with bacteriorhodopsin 10

11. Collecting Data Articles Oldfashioned library work Online libraries (PubMed) Online databases GPCRDB Websites Different GPCR-groups 11

12. Making Alignments Structural alignment rhodopsin/bacteriorhodopsin ---------- -WIWLALGTA LMGLGTLYFL VK-------- BRh ----PWQFSM LAAYMFLLIM LGFPINFLTL YVTVQ----- Rh Comparing with alignments made by other GPCR-experts ---------- -WIWLALGTA LMGLGTLYFL VK-------- BRh ----PWQFSM LAAYMFLLIM LGFPINFLTL YVTVQ----- Rh ---------P EWIWLALGTA LMGLGTLYFL VKGM------ BRh Vriend ---------Q FSMLAAYMFL LIMLGFPINF LTLY------ Rh Vriend Difference: +3 Helix 3 means trouble Differences were larger then +10. Complete alignment 12

13. Structure validation with WHAT-IF I Structure predictions by Baldwin et al. Electron density maps 493 GPCR (a.a.)sequences Helical orientation Interacting residues Helical orientation as predicted was correct Only a few residues interact: :17 GP VII:18 :18 NA II:11D II:14 :21 VA II:11Y VII:21 13

14. Structure validation with WHAT-IF II Structure predictions by Thirstrup et al. Construction of zinc binding site  -opioid receptor Helical orientation Helix-helix interactions Measured distances between zinc ion and residues too large; even with the use of the ‘tors’ command 14

15. Structure validation with WHAT-IF III Structure predictions by Greenhalgh et al. Spin label; electron paramagnetic resonance spectroscopy Mapping residue positions (relative to aqueous boundaries) ResidueContact Greenhalgh et al. ContactWhatIFDifference Arg-82Extracellularabout 5Tyr-796.11.1 Asp-85Extracellularabout 9Tyr-7910.81.8 Asp-96Intracellularwithin 7Val-1018.81.8 Differences are within range; spin-labeling could be a reasonably safe way to predict the structure of membrane proteins Distances for bacteriorhodopsin (in Å): 15

16. Conclusions Predicting a structure with such low level of homology is very hard Most predictions are in the right direction, but still need some refinement Availability of real data (e.g. electron density maps) improves structure prediction 16

17. Take a look at our website! http://go.to/gpcr 17

18. Learning points Programming in Python What-IF GPCRs Website building (e.g. CGI)