by Siavoush Dastmalchi Tabriz University of Medical Sciences Tabriz-Iran

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

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

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 1 2 3 4 3 4 N F 1 2 3 4 OR

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

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

11. Profiles–3D algorithmfromInsightII molecular modeling packageDeveloped in David Eisenberg’s lab.

12. Area buried (Å2) 0 40 80 120 E P2 B3 0.80 0.40 0.00 P1 Fraction polar B2 B1 Environmental classes

13. 3D–1D scoring table RESIDUES CLASSES

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

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 1 2 3 4 5 6 7

23. RMSD comparison of Rhodopsin models generated using different methods with its crystal structure

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

29. 7 2 1 4 5 6 3 hGALR1-GALANIN COMPLEX Extracellular Intracellular

30. 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. Summary & Conclusion

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