1. by Siavoush Dastmalchi Tabriz University of Medical Sciences Tabriz-Iran Modelling the Structures of G Protein-Coupled Receptors Aided by Three-Dimensional Validation

2. Biological functions of IMPs: Channels and Pumps (Cl - channels, Na + /K + - ATPase) Maintaining appropriate contact (fibronectin receptors) Signal transducing proteins (GPCRs) Respiratory enzyme complexes Toxin and pathogen entry regulating proteins (neuraminidase)

3. Sparse structural knowledge about IMPs Few high-resolution 3D structures are available Difficult to grow crystals IMPs are abundant 35-40% of yeast genes and ~20% of all human genes code for IMPs

5. Structurally solved IMPs: Bacteriorhodopsin Cytochrome C oxidase Light harvesting complex Photosynthetic reaction center Porin

6. IMP graphics

7. Required information: Location of transmembrane (TM) segments Basic topology of TM domain Orientation of TM segments Relative depth of TM segments in lipid

8. 1 2 3 4 1234 12 34 N F OR

9. Baldwin(1997) model Palczewski (2000) 2.8Å Bovine Rhodopsin Extracellular Intracellular

10. Palczewski et al. 2000 Science 289: 739-745.

11. Profiles–3D algorithm from InsightII molecular modeling package Developed in David Eisenberg’s lab.

12. 0.80 0.40 0.00 EP2P2 P1P1 B1B1 B2B2 B3B3 0 40 80 120 Area buried (Å 2 ) Fraction polar Environmental classes

13. 3D–1D scoring table CLASSES RESIDUES

14. Valpred Graphs Tables Graphics Options

15. Dastmalchi et al. 2002 Mol. Simulation 28: 845-851.

16. Distribution of raw Profiles-3D and lipid-corrected compatibility score values of 493 GPCRs models represented by open circle and closed circle respectively.

17. Improvement of Compatibility Score It is clear that by simulation of a lipid environment around the model the total compatibility score is increased. This is an indication that for reasonable modelling of IMPs, the correct environment needs to be used in term of model building and verification.

18. 4 3 5 6 7 GPCR Helical Bundle N C S-S P N-linked glycosylation Disulphide bond Covalently attached palmitate Phosphorylation P P G protein

19. Average of normalised lipid-corrected compatibility scores for the models of GPCRs vs rotation of individual helices.

20. Total of lipid-corrected compatibility scores of the human galanin receptor model vs rotation of individual helices.

21. Helix 12345671234567

23. RMSD comparison of Rhodopsin models generated using different methods with its crystal structure MethodReferenceRMSD (Å) REPIMPS3.3 PREDICTShacham et al. Med Res Rev (2001) 21: 472. 2.9 ROSETTAYarov-Yarovoy et al. Proteins (2006) 62: 1010. 3.8 BaldwinBaldwin et al. J Mol Biol (1997) 272: 144. 3.2

25. Helical wheel representation of helical segments 1-4 of hGalR1

29. 12 7 6 4 3 5 Extracellular Intracellular hGALR1-GALANIN COMPLEX

30. Summary & Conclusion Our method can be used for evaluation of 3D models of GPCRs Advantages of this method lies in its 3D characteristic & environmental sensitivity In the case GPCRs, we used simple modelling procedure & the sampling method didn’t cover all possible conformational space Predicting the positions and incorporating the possible irregular geometries in the helical regions, and using sampling methods in positioning different segments of TMHs, followed by scoring the models with our method may further improve the quality of the models. Results provided here suggest that probably there is no unique consensus template for modeling GPCRs. However, Baldwin model or even the crystal structure of rhodopsin can be a good starting point. Meanwhile, the quality of the model can be assessed and improved by taking in to account environmental considerations.

31. Acknowledgments Thank you all Thanks to the Organizers of InCoB2007 Dr Bret Church (Sydney University) Dr Michael Morris (Sydney University)