Post on 30-May-2018
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ProteinShop: A Tool for Protein
Structure Prediction andModeling
Silvia Crivelli
Computational Research Division
Lawrence Berkeley National Laboratory
8/14/2019 ProteinShop: A Tool for Protein Structure Prediction and Modeling
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The Protein Structure Prediction
ProblemTo determine how proteins, the building
blocks of living cells, fold themselves into
three-dimensional shapes that define the
role they play in life.
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Importance of Protein Structure
Prediction• The shape of a protein determines its function.
• Knowledge of structure is used in many ways:
– Drug design – Design of synthetic proteins
– Re-engineering defective proteins
• Genome projects are providing sequences for many proteins whose structure will need to bedetermined.
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Protein Structures
ProGly Leu Ser
Proteins consist of a long chain of
amino acids, the primary structure
N
O H
R H
N
O H
R H
N
O H
R H
N
O H
R H
N
OH
R H
N
OH
R H
N
OH
R H
N
OH
R H
Side chain
H-bond
Backbone
Amino acid
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Protein Structures
ProGly Leu Ser
Proteins consist of a long chain of
amino acids, the primary structure
The constituent amino acids may
encourage hydrogen bonding thatform regular structures, called
secondary structures
The secondary structures fold
together to form a compact
3-dimensional shape, called
the tertiary structure
α -helix β -sheet
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The problem can be formulated as a global
minimization problem, as it is assumed that thetertiary structure occurs at the global minimum of
the free energy function of the primary sequence
Ab Initio Approach
Our Goal: To provide an approach that relies more on physical
principles than on information from known proteins
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Ab Initio MethodTertiary structure is
believed to minimize potential energy:
Min V MM
( x )
where x = atom coordinates
Difficulties: Proposed energy function may not
match nature
O(en2) local minima
Very large parameter space
e.g., modestly sized protein100 amino acids
~ 1,600 atoms
~ 4,800 variables
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Secondary Structure Predictions
in Phase 1
SKIGIDGFGRIGRLVLRAALSCGAQ
SKIGIDGFGRIGRLVLRAALSCGAQ
CBBBB BCCCAAAAAAACCCBBBBBC
1135522356789992888566733
Sequence:
Type:
Weight:
Sequence:
Servers predict secondary
structure likely to be in a
target protein based on alarge database of known
proteins.
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Matching the predicted strands is a
combinatorial problem
Which strands are paired?
Which orientation?
? ??
parallel anti-parallel
Which residues are paired?
odd even
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There are n!2 n-2 possible
n-stranded motifs
96 motifs for n=4
960 motifs for n=5
It takes weeks tocreate some of theseconfigurations usingconstrained local
minimizations!
Distribution of Beta Sheets in Proteins with Applications to Structure Prediction
Ruckzinski, Kooperberg, Bonneau, and Baker, Proteins 48,2002
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CASP4 Competition
• Fourth community-wide experiment on the
Critical Assessment of Techniques for Protein
Structure Prediction (2000)
• Our group predicted 8 proteins
•Largest protein had 240 aa•Most complex fold had 2 β-strands
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ProteinShop
• Interactive tool for protein manipulation
• Designed to quickly create initial configurations
• It takes weeks to create a number of configurations
using constrained minimizations
• It takes a few hours to create the same
configurations with ProteinShop
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Phase 1 with ProteinShop
Phase 1
Amino Acid Sequence
Phase 2
Initial Configurations
Final Configuration
2nd ary Structure
Prediction
Geometry
Generation
Structure Sequence
Direct
Manipulation
Pre-configuration
Initial Configurations
ProteinShop
takes minutes
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CASP4 Competition (before ProteinShop)
CASP5 Competition (with ProteinShop)
•Our group predicted 20 proteins
•Largest protein had 417 aa
•Most complex fold had 13 β-strands
•Our group predicted 8 proteins
•Largest protein had 240 aa
•Most complex fold had 2 β-strands
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Phase 2
Phase 1
Amino Acid Sequence
Phase2: Global
Optimization
Initial Configurations
Final Configuration
Subspace
Selection
Initial Configurations
Subspace
Optimization
Candidate
Selection
Final Configuration
Takes months toconverge usinghundreds of processors onSeaborg!
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Phase 2 with ProteinShop
Phase 1
Amino Acid Sequence
Phase2: Global
Optimization
Initial Configurations
Final Configuration
Subspace
Selection
Initial Configurations
Subspace
Optimization
Candidate
Selection
Final Configuration
Monitoring
System
Direct
Manipulation
Steering
System
Will reducecomputation time
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Monitoring System
• Monitor progress of overall optimization/eachoptimization process
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Monitoring System
• Monitor progress of overall optimization/each
optimization process
• Alert user to important events during optimization
• A sudden drop in internal energy
• A group of processes getting stuck
• Test new heuristics for expanding nodes of the
tree
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Steering System
• Change configurations during optimization toaccount for developments not anticipated during
Phase 1
• Manipulate proteins that don’t seem to be realistic
or that are stuck in a local minimum
• Allow pruning of the optimization tree•Assign multiple processes to a configuration that just had
a drop in internal energy
•Assign stuck processes to other configurations
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Plans for the Future
Use of the monitoring and steering
features to develop and test a new
method for protein structure prediction
Compete in CASP6 (Critical Assessment
of Techniques for Protein Structure Prediction)
Expand and enhance ProteinShop
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O. Kreylos, N. Max, B. Hamann,
S. Crivelli, and W. Bethel.
Interactive Protein Manipulation,
Winner of the Best ApplicationAward IEEE Visualization 2003,
Seattle.
ProteinShop
Available to academic and non-profit organizations
proteinshop.lbl.gov