An Integrated Approach to ProteinProtein Docking
Zhiping Weng
Department of Biomedical Engineering
Bioinformatics Program
Boston University
What is Protein Docking?
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Biomedical Engineering
Protein docking is the computational
determination of protein complex structure
from individual protein structures.
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Motivation
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Biomedical Engineering
• Biological activity depends on the specific
recognition of proteins.
• Understand protein interaction networks in a cell
• Yield insight to thermodynamics of molecular
recognition
• The experimental determination of protein-protein
complex structures remains difficult.
Ubiquitination
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Biomedical Engineering
Experimental Tools for Studying
Protein-Protein Interactions
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• 3-D structures of protein-protein
complexes: X-ray crystallography & NMR
• Binding affinity between two proteins: SPR,
titration assays
• Mutagenesis and its affect on binding
• Yeast 2-hybrid system
• Protein Chips?
Computational Tools for Studying
Protein-Protein Interactions
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• Protein docking
• Binding affinity calculation
• Analysis of site-specific mutation
experiments
• Protein design
• The kinetics of protein-protein interactions
Protein-Protein Interaction
Thermodynamics
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G   RT ln
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G : Binding Free Energy
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Biomedical Engineering
The Lowest Binding Free
Energy G
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General Derivations
Two kinds of docking problems
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• Bound docking
The complex structure is known. The receptor and
the ligand in the complex are pulled apart and
reassembled.
• Unbound docking
Individually determined protein structures are used.
Challenges
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Biomedical Engineering
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Large search space
Imperfect understanding of thermodynamics
Protein flexibility
Heterogeneities in protein interactions
Divide and Conquer
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Initial stage of unbound docking
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Assume minimum binding site information
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Try to predict as many near-native structures
(hits) as possible in the top 1000, for as many
complexes as possible
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Post-processing
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Re-rank the 1000 structures in order to pick out
near-native structures
Energy Components
An Effective Binding Free
Energy Function
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ΔG=ΔE vdW +ΔG desol +ΔE elec +ΔG const
ΔE vdW : van der Waals energy; Shape complementarity
ΔG desol : Desolvation energy; Hydrophobicity
ΔE elec : Electrostatic interaction energy
ΔG const : Translational, rotational and vibrational free energy changes
ΔG desol =  N i ΔG i
i
N i : Number of atoms of type i
ΔG i : Desolvation energy for an atom of type i
Fast Fourier Transform
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FFT
IFFT
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Correlation
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FFT
Surface
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Interior
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Binding Site
Increase the speed by 107
DOCK by Kuntz et al.
Evaluate Performance
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• Gold Standard: Crystal structure of the complex
• A near-native structure (hit):
RMSD of Ca after superposition < 2.5 Å
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RMSD j 
 (x
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 x ic ) 2  ( yij  yic ) 2  ( zij  zic ) 2
i 1
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• Success rate: Given some number of
predictions, percentage of complexes with at
least one hit
Docking Benchmark
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25
55 non-redundant complexes
http://zlab.bu.edu/~rong/dock/
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20
16
15
10
10
6
5
0
Enzyme/Inihbitor
Antibody/Antigen
Others
Difficult Cases
A Novel Shape Complementarity Function
100%
Grid-based shape complementarity (GSC)
GSC+Desolvation+Electrostatics
Pairwise shape complementarity (PSC)
PSC +Desolvation+Electrostatics
90%
80%
Success Rate
70%
60%
50%
40%
30%
20%
10%
0%
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100
Number of Predictions
1000
Post-Processing Using RDOCK
CAPRI Results
Total
Target
Contacts
Top Predictions
Our
Prediction
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52
17 (1st)
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2
52
27 (2nd)
50 (1st)
3
62
45 (1st), 43 (2nd)
37 (3rd)
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58
1 (1st)
0
5
64
10 (1st)
4 (2nd)
6
65
60(1st)
18
37
30(2nd,3rd),
29(4th,5th)
31(1st)
7
Target 2: Antibody/VP6
Red: Crystal Structure
Blue: Prediction 50/52; 1st
Target 7: T Cell Receptor / Toxin
Red: Crystal Structure
Blue: Prediction 31/37, 1st
Target 3: Antibody/Hemagglutinin
Red: Crystal Structure
Blue: Prediction 37/62, 3rd
Target 6: Camelide Antibody/a amylase
Red: Crystal Structure
Blue: Prediction 18/65
Target 1:Hpr/HPrK
Red: Crystal Structure
Blue: Prediction 5/52
Summary
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• Conformational change tolerant target
functions are needed for unbound docking
• We need to balance shape complementarity,
desolvation, electrostatics components
• If we submit 10 predictions, we have a 60%
success rate.
Future Work
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• An automatic protein-protein docking
server
• Large scale comparison of all docking
algorithms on the benchmark
• Post processing with binding site
information, conformation space search,
clustering and detailed free energy
calculation
• Make predictions!