1. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modelling Thomas Blicher Center for Biological Sequence Analysis

2. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Why Do We Need Homology Modelling?  Ab Initio protein folding (random sampling): –100 aa, 3 conf./residue gives approximately 10 48 different overall conformations!  Random sampling is NOT feasible, even if conformations can be sampled at picosecond (10 -12 sec) rates. –Levinthal’s paradox  Do homology modelling instead.

3. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU How Is It Possible?  The structure of a protein is uniquely determined by its amino acid sequence (but sequence is sometimes not enough): –prions –pH, ions, cofactors, chaperones  Structure is conserved much longer than sequence in evolution. –Structure > Function > Sequence

4. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU How Often Can We Do It?  There are currently ~40000 structures in the PDB (but only ~4000 if you include only ones that are not more than 30% identical and have a resolution better than 3.0 Å).  An estimated 25% of all sequences can be modeled and structural information can be obtained for ~50%.

5. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Worldwide Structural Genomics  ”Fold space coverage”  Complete genomes  Signaling proteins  Improving technology  Disease-causing organisms  Model organisms  Membrane proteins  Protein-ligand interactions

6. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Structural Genomics in North America  10 year $600 million project initiated in 2000, funded largely by NIH.  AIM: structural information on 10000 unique proteins (now 4-6000), so far 1000 have been determined.  Improve current techniques to reduce time (from months to days) and cost (from $100.000 to $20.000/structure).  9 research centers currently funded (2005), targets are from model and disease-causing organisms (a separate project on TB proteins).

7. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modeling for Structural Genomics Roberto Sánchez et al. Nature Structural Biology 7, 986 - 990 (2000)

8. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU How Well Can We Do It? Sali, A. & Kuriyan, J. Trends Biochem. Sci. 22, M20–M24 (1999)

9. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU How Is It Done?  Identify template(s) – initial alignment  Improve alignment  Backbone generation  Loop modelling  Side chains  Refinement  Validation 

10. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Template Identification  Search with sequence –Blast –Psi-Blast –Fold recognition methods  Use biological information  Functional annotation in databases  Active site/motifs

11. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Alignment

12. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU FDICRLPGSAEAVC F6-20-3-22 -3-2-3-20-3 N 2-2 0 02010 V0 2 2 0 05-2 C R 5001 0 -2 T P E-32-2-30-2101151-3 A-20-2 1015150-2 I0-35-2 2 -22-2 C-3-2 8 -3 -2-2-3-2 8 1 2 3 4 5 6 7 8 9 10 11 12 13 14 PHE ASP ILE CYS ARG LEU PRO GLY SER ALA GLU ALA VAL CYS PHE ASN VAL CYS ARG THR PRO --- --- --- GLU ALA ILE CYS PHE ASN VAL CYS ARG --- --- --- THR PRO GLU ALA ILE CYS

13. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU 1 2 3 4 5 6 7 8 9 10 11 12 13 14 PHE ASP ILE CYS ARG LEU PRO GLY SER ALA GLU ALA VAL CYS PHE ASN VAL CYS ARG THR PRO --- --- --- GLU ALA ILE CYS PHE ASN VAL CYS ARG --- --- --- THR PRO GLU ALA ILE CYS FDICRLPGSAEAVC F6-20-3-22 -3-2-3-20-3 N 2-2 0 02010 V0 2 2 0 05-2 C-3-2 8 -3 -2-2-3-2 8 R 5001 0 -2 T 00000 20100 P-20 -30-2800111-3 E 2-2-30-2101151-3 A-20-2 1015150-2 I0-35-2 2 -22-2 C-3-2 8 -3 -2-2-3-2 8

14. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU 1 2 3 4 5 6 7 8 9 10 11 12 13 14 PHE ASP ILE CYS ARG LEU PRO GLY SER ALA GLU ALA VAL CYS PHE ASN VAL CYS ARG THR PRO --- --- --- GLU ALA ILE CYS PHE ASN VAL CYS ARG --- --- --- THR PRO GLU ALA ILE CYS From ”Professional Gambling” by Gert Vriend http://www.cmbi.kun.nl/gv/articles/text/gambling.html Improving the Alignment

15. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Template Quality  Selecting the best template is crucial!  The best template may not be the one with the highest % id (best p-value…) –Template 1: 93% id, 3.5 Å resolution  –Template 2: 90% id, 1.5 Å resolution

16. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU The Importance of Resolution high low 4 Å 2 Å 3 Å 1 Å

17. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Ramachandran Plot  Allowed backbone torsion angles in proteins N H Amino acid residue

18. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Template Quality – Ramachandran Plot NMR structure – low quality data… X-ray structure – good data.

19. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Backbone Generation  Generate the backbone coordinates from the template for the aligned regions.  Several programs can do this, most of the groups at CASP6 use Modeller: http://salilab.org/modeller/modeller.html

20. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Loop Modelling  Knowledge based: –Searches PDB for fragments that match the sequence to be modelled (Levitt, Holm, Baker etc.).  Energy based: –Uses an energy function to evaluate the quality of the loop and minimizes this function by Monte Carlo (sampling) or molecular dynamics (MD) techniques.  Combination

21. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Loops – the Rosetta Method  Find fragments (10 per amino acid) with the same sequence and secondary structure profile as the query sequence.  Combine them using a Monte Carlo scheme to build the loop. David Baker et al.

22. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Side Chains  Side chain rotamers are dependent on backbone conformation.  Most successful method in CASP6 was SCWRL by Dunbrack et al.: –Graph-theory knowledge based method to solve the combinatorial problem of side chain modelling. http://dunbrack.fccc.edu/SCWRL3.php

23. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Side Chains  Prediction accuracy is high for buried residues, but much lower for surface residues –Experimental reasons: side chains at the surface are more flexible. –Theoretical reasons: much easier to handle hydrophobic packing in the core than the electrostatic interactions, including H-bonds to waters.

24. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Side Chains  If the seq. id is high, the networks of side chain contacts may be conserved, and keeping the side chain rotamers from the template may be better than predicting new ones.

25. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Refinement  Energy minimization  Molecular dynamics –Big errors like atom clashes can be removed, but force fields are not perfect and small errors will also be introduced – keep minimization to a minimum or matters will only get worse.

26. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Error Recovery  If errors are introduced in the model, they normally can NOT be recovered at a later step –The alignment can not make up for a bad choice of template. –Loop modeling can not make up for a poor alignment.  If errors are discovered, the step where they were introduced should be redone.

27. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Validation  Most programs will get the bond lengths and angles right.  The Ramachandran plot of the model usually looks pretty much like the Ramachandran plot of the template (so select a high quality template).  Inside/outside distributions of polar and apolar residues can be useful.

28. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Validation – ProQ Server  ProQ is a neural network based predictor that based on a number of structural features predicts the quality of a protein model.  ProQ is optimized to find correct models in contrast to other methods which are optimized to find native structures. Arne Elofssons group: http://www.sbc.su.se/~bjorn/ProQ/

29. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Structure Validation  ProCheck http://www.biochem.ucl.ac.uk/~roman/procheckhttp://www.biochem.ucl.ac.uk/~roman/procheck/proc heck.html  WhatIf server http://swift.cmbi.kun.nl/WIWWWI/

30. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modelling Servers  Eva-CM performs continous and automated analysis of comparative protein structure modeling servers  A current list of the best performing servers can be found at: http://cubic.bioc.columbia.edu/eva/doc/intro_cm.html

31. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU The Hardest Target in CASP6  Only 8% sequence id between target and template. Dunbrack, Wang & Jin (2004) CASP6 Fold Recognition Assessment

32. CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Summary  Successful homology modelling depends on the following: –Template quality –Alignment (add biological information) –Modelling program/procedure (use more than one)  Always validate your final model!