Homology Modelling

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Homology Modelling

• Thomas Blicher
• Center for Biological Sequence Analysis

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Why Do We Need Homology Modelling?

• Ab Initio protein folding (random sampling)
• 100 aa, 3 conf./residue gives approximately 1048
  different overall conformations!
• Random sampling is NOT feasible, even if
  conformations can be sampled at picosecond (10-12
  sec) rates.
• Levinthals paradox
• Do homology modelling instead.

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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 gt Function gt Sequence

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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.

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Worldwide Structural Genomics

• Fold space coverage
• Complete genomes
• Signaling proteins
• Improving technology
• Disease-causing organisms
• Model organisms
• Membrane proteins
• Protein-ligand interactions

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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).

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Homology Modeling for Structural Genomics
Roberto Sánchez et al. Nature Structural Biology
7, 986 - 990 (2000)
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How Well Can We Do It?
Sali, A. Kuriyan, J. Trends Biochem. Sci. 22,
M20M24 (1999) 
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How Is It Done?

• Identify template(s) initial alignment
• Improve alignment
• Backbone generation
• Loop modelling
• Side chains
• Refinement
• Validation ?

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Template Identification

• Search with sequence
• Blast
• Psi-Blast
• Fold recognition methods
• Use biological information
• Functional annotation in databases
• Active site/motifs

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Alignment
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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
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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
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Improving the Alignment
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
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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 ?

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The Importance of Resolution
4 Å
3 Å
2 Å
1 Å
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Ramachandran Plot

• Allowed backbone torsion angles in proteins

Amino acid residue
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Template Quality Ramachandran Plot
X-ray structure good data.
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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

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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

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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.

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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

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Side Chains

• Prediction accuracy is high for buried residues,
  but much lower for surface residues
• Experimental reasonsside chains at the surface
  are more flexible.
• Theoretical reasonsmuch easier to handle
  hydrophobic packing in the core than the
  electrostatic interactions, including H-bonds to
  waters.

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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.

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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.

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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.

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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.

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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/
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Structure Validation

• ProCheck
• http//www.biochem.ucl.ac.uk/roman/procheck/proch
  eck.html
• WhatIf server
• http//swift.cmbi.kun.nl/WIWWWI/

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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.ht
  ml

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The Hardest Target in CASP6

• Only 8 sequence id between target and template.

Dunbrack, Wang Jin (2004) CASP6 Fold
Recognition Assessment
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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!