1. Lab 10.21 Lab 10.2: Homology Modeling Lab Boris Steipe boris.steipe@utoronto.ca http://biochemistry.utoronto.ca/steipe Departments of Biochemistry and Molecular and Medical Genetics Program in Proteomics and Bioinformatics University of Toronto

2. Lab 10.22 Concepts 1.Sequence alignment is the single most important step in homology modeling. 2.Reasons to model need to be defined. 3.Fully automated homology modeling services perform well. 4.SwissModel in practice.

3. Lab 10.23 Concept 1: Sequence alignment is the single most important step in homology modeling.

4. Lab 10.24 Superposition vs Alignment The coordinates of two proteins are “superimposed” in space. An alignment may be derived by correlated pairs of alpha-carbons. A superposition may differ from an optimized symbolic alignment...

5. Lab 10.25 Insert of 4 residues Optimal sequence aligment gktlit nfsqehip gktlisflyeqnfsqehip Optimal structure alignment (blue=helix) gktlitnfsq ehip gktlisflyeqnfsqehip

6. Lab 10.26 Off by 1, Off by 4 A shift in alignment of 1 residue corresponds to a skew in the modeled structure of about 4 Å (3.8 Å is the inter-alpha carbon distance) Nothing you can do AFTER an alignment will fix this error (not even molecular dynamics). 3.8Å

7. Lab 10.27 Alignment is the limiting step for homology model accuracy No amount of forcefield minimization will put a misaligned residue in the right place ! HOMSTRAD @ CASP4: Williams MG et al. (2001) Proteins Suppl.5: 92-97

8. Lab 10.28 Indels (inserts or deletions) Observations of known similarities in structures demonstrate that uniform gap penalty assumptions are NOT BIOLOGICAL. Indels are most often observed in loops, less often in secondary structure elements When they do not occur in loops, there is usually a maintenance of helical or strand properties.

9. Lab 10.29 Can we do better with the gap assumption? Required: position specific gap penalties One approach: implemented in Clustal as secondary structure masks Get secondary structure information, convert it to Clustal mask format. (Easy - read documentation !)

10. Lab 10.210 Secondary structure from PDB.... (Algorithm ?)

11. Lab 10.211 Secondary structure from RasMol.... (DSSP !)

12. Lab 10.212 Concept 2: Reasons to model need to be defined.

13. Lab 10.213 Use of homology models Interpreting homology models: biochemical inference from 3D similarity Bonds Angles, plain and dihedral Surfaces, solvent accessibility Amino acid functions, presence in structure patterns Spatial relationship of residues to active site Spatial relationship to other residues Participation in function / mechanism Static and dynamic disorder Electrostatics Conservation patterns (structural and functional) Posttranslational modification sites

14. Lab 10.214 Abuse of homology models Modelling structures that cannot / will not be verified Analysing geometry of model Interpreting loop structures

15. Lab 10.215 Databases of Models Don’t make models unless you check first... Swiss-Model repository 64,000 models based on 4000 structures and Swiss-Prot proteins ModBase Made with "Modeller" - 15,000 reliable models for substantial segments of approximately 4,000 proteins in the genomes of Saccharomyces cerevisiae, Mycoplasma genitalium, Methanococcus jannaschii, Caenorhabditis elegans, and Escherichia coli.

16. Lab 10.216 Concept 3: Fully automated services perform well.

17. Lab 10.217 Homology Modeling Software? Freely available packages perform as good as commercial ones at CASP (Critical Assessment of Structure Prediction) Swiss Model (tutorial) Modeller ( http://guitar.rockefeller.edu )

18. Lab 10.218 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities BLASTP against EX-NRL 3D

19. Lab 10.219 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates Identity: > 25% Expected model : > 20 resid.

20. Lab 10.220 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments Select regions of similarity and match in coordinate- space (EXPDB).

21. Lab 10.221 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones Compute weighted average coordinates for backbone atoms expected to be in model.

22. Lab 10.222 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones 5. Build loops Pick plausible loops from library, ligate to stems; if not possible, try combinatorial search.

23. Lab 10.223 Bridge with overlapping pieces from pentapeptide fragment library, anchor with the terminal residues and add the three central residues. Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones 5. Build loops 6. Bridge incomplete backbones

24. Lab 10.224 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones 5. Build loops 6. Bridge incomplete backbones 7. Rebuild sidechains Rebuild sidechains from rotamer library - complete sidechains first, then regenerate partial sidechains from probabilistic approach.

25. Lab 10.225 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones 5. Build loops 6. Bridge incomplete backbones 7. Rebuild sidechains 8. Energy minimize Gromos 96 - Energy minimization

26. Lab 10.226 Swiss-Model steps: Peitsch M & Guex N (1997) Electrophoresis 18: 2714 e-mail results 1. Search for sequence similarities 2. Evaluate suitable templates 3. Generate structural alignments 4. Average backbones 5. Build loops 6. Bridge incomplete backbones 7. Rebuild sidechains 8. Energy minimize 9. Write Alignment and PDB file

27. Lab 10.227 Swissmodel in comparison 3D-Crunch: 211,000 sequences -> 64,000 models Controls: >50 % ID: ~ 1 Å RMSD 40-49% ID: 63% < 3Å 25-29% ID: 49% < 4Å Guex et al. (1999) TIBS 24:365-367 EVA: Eyrich et al. (2001) Bioinformatics 17:1242-1243 (http://cubic.bioc.columbia.edu/eva) Manual alternatives: Modeller... Automatic alternatives: SwissModel sdsc1 3djigsaw pcomb_pcons cphmodels easypred # 1 for RMSD and % correct aligned, #2 for coverage

28. Lab 10.228 What structure elements change between similar sequence? Subtle changes in protein backbone path Changes in amino acid side-chain rotamer orientation backbone dependent Loops added or truncated Model may be incomplete

29. Lab 10.229 Concept 4: SwissModel in practice.

30. Lab 10.230 SwissModel... first approach mode http://www.expasy.org/swissmod

31. Lab 10.231... enter the ExPDB template ID...

32. Lab 10.232... run in Normal Mode (Except if defining a DeepView project )...

33. Lab 10.233... successful submission. Results come by e-mail.

34. Lab 10.234 Optimal sequence alignment http://cbrmain.cbr.nrc.ca/EMBOSS/index.html [...] # Matrix: EBLOSUM35 # Gap_penalty: 10.0 # Extend_penalty: 0.5 # # Length: 122 # Identity: 36/122 (29.5%) # Similarity: 55/122 (45.1%) # Gaps: 28/122 (23.0%) # Score: 150.5 [...] #======================================= 23 LNNKKTIAEGRRIPISKAVENPTATEIQDVCSAVGLNVFLEKNKMYSREW 72 |:.||:.|||||||...||.|....|:.:....:||. |..:.|.|.:.| 11 LDSKKSRAEGRRIPRRFAVPNVKLHELVEASKELGLK-FRAEEKKYPKSW 59 73 NRDVQYRGRVRVQLKQEDGSLCLVQFPSRKSVMLYAAEMIPKLKTRTQKT 122.:..|||.|:.:.::..:|:..|..|.::: 60 ---WEEGGRVVVEKR-----------GTKTKLMIELARKIAEIR------ 89 123 GGADQSLQQGEGSKKGKGKKKK 144 :|..:| ||.|.|||| 90 ---EQKREQ----KKDKKKKKK 104

35. Lab 10.235 Optimal structural superposition 1.4Å in 32 res.

36. Lab 10.236 Questions ? Feedback ? boris.steipe@utoronto.ca http://biochemistry.utoronto.ca/steipe/