1. Practical session 2b Introduction to 3D Modelling and threading 9:30am-10:00am 3D modeling and threading 10:00am-10:30am Analysis of mutations in MYH6 Miguel Andrade Max Delbrück Center for Molecular Medicine Miguel.andrade@mdc-berlin.de

2. Introduction Protein tertiary structure Secondary structure elements fold together

3. Introduction Protein quaternary structure Folded proteins form a complex

4. Protein domains are structural units (average 160 aa) that share: Function Folding Evolution Proteins normally are multidomain (average 300 aa) Introduction

5. Protein domains are structural units (average 160 aa) that share: Function Folding Evolution Proteins normally are multidomain (average 300 aa) Introduction

6. X-ray crystallography (70,714 in PDB) need crystals Nuclear Magnetic Resonance (NMR) (9,312) proteins in solution lower size limit (600 aa) Electron microscopy (422) Low resolution (>5A) Determination of protein structure

7. resolution 2.4 A

8. Determination of protein structure resolution 2.4 A

9. Structural genomics Currently: 81K 3D structures from around 27K seqs 16M sequences in UniProt only 0.17%!

10. Structural genomics Currently: 81K 3D structures from around 27K seqs 16M sequences in UniProt 50% sequences covered (25% in 1995) only 0.17%!

11. Strategy for analysis Query Sequence Yes 3D Modeling by homology No 2D Prediction 3D Ab initio 3D Threading Similar to PDB sequence? Predict domains Cut

12. 3D structure prediction Approaches Class 1 Comparative modeling Class 2 Ab initio Need sequence only Need similarity to a known structure Threading

13. 3D structure prediction Approaches Search for sequences of known structure similar to target Comparative modeling (30% to 50% id) Model from template core regions and from loops and side chains of structures that might be unrelated Atom coordinates from conserved residues Optimize distance constraints derived from sequence-template alignment Extra methods for loops, turns, and side chains

14. 3D structure prediction Approaches Thread target sequence through a library of known folds. Select right fold based on energy considerations More computational cost – but detect more distant relationships Threading (identity can be lower than 30%)

15. 3D structure prediction Approaches Explore conformational space Limit the number of atoms Break the problem into fragments of sequence Optimize hydrophobic residue burial and pairing of beta-strands Limited success Ab initio

16. Relation between sequence identity and accuracy/applications From: Baker and Sali (2001) Science

17. 3D structure prediction Applications: target design Query sequence catalytic center known 3D Leu Gly model 3D by homology Gly Lys + similar to LG GK

18. 3D structure prediction Applications: fit to low res 3D Query sequence 1 low resolution 3D (electron microscopy) Query sequence 2

19. 3D structure prediction GenTHREADER David Joneshttp://bioinf.cs.ucl.ac.uk/psipred/ Input sequence Relatively quick, 5 minutes GenTHREADER Jones (1999) J Mol Biol

20. Output GenTHREADER 3D structure prediction GenTHREADER

21. 3D structure prediction Phyre http://www.sbg.bio.ic.ac.uk/phyre2/ Kelley et al (2000) J Mol Biol Kelley and Sternberg (2009) Nature Protocols

22. 3D structure prediction I-Tasser Jeffrey Skolnick Tasser Yang Zhang I-Tasser Lee and Skolnick (2008) Biophysical Journal Roy et al (2010) Nature Methods Threading Fold 66% sequences <200 aa long of low homology to PDB Just submit your sequence and wait… (some days) Output are predicted structures (PDB format)

23. 3D structure prediction I-Tasser Roy et al (2010) Nature Methods

24. 3D structure prediction I-Tasser http://zhanglab.ccmb.med.umich.edu/I-TASSER/

25. 3D structure prediction I-Tasser

26. 3D structure prediction QUARK http://zhanglab.ccmb.med.umich.edu/QUARK/

27. 3D structure prediction MODbase Andrej Salihttp://modbase.compbio.ucsf.edu/ Pieper et al (2011) Nucleic Acids Research

28. 3D structure prediction MODbase