# Presentation: 515719

## ProteinShop: A Tool for Protein Structure Prediction and Modeling

** ****	****	****      ****Silvia Crivelli**
-     Computational Research Division
-     Lawrence Berkeley National Laboratory

## The Protein Structure Prediction Problem

- To determine how proteins, the building
- blocks of living cells, fold themselves into
- three-dimensional shapes that define the
- role they play in life.

## 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 be determined.

## Protein Structures

- Pro

- Gly

- Leu

- Ser

- Proteins consist of a long chain of
- amino acids, the primary structure

## Protein Structures

- Pro

- Gly

- Leu

- Ser

- Proteins consist of a long chain of
- amino acids, the primary structure

- The constituent amino acids may encourage hydrogen bonding that form regular structures, called secondary structures

- The secondary structures fold
- together to form a compact
- 3-dimensional shape, called
- the tertiary structure

- -helix

- -sheet

## Ab Initio Approach

- The problem can be formulated as a global minimization problem, as it is assumed that the tertiary structure occurs at the global minimum of the free energy function of the primary sequence

- Our Goal: To provide an approach that relies more on physical
- principles than on information from known proteins

## Ab Initio Method

- Tertiary structure is
- believed to minimize potential energy:
**Min  *****V******MM*****(*****x*****)**
- where *x* = atom coordinates

- Difficulties:

## The Search Algorithm

- Given the amino acid sequence of a
- protein, find the global minimum of
- the free energy function.

- Generate
- Starting
- Configurations

- Global
- Optimization

- Phase 1

- Phase 2

## 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 a large database of known proteins.

## Matching the predicted strands is a 

- combinatorial problem

- Which _strands_ are paired?

- Which _orientation_?

- ?

- ?

- ?

- parallel

- anti-parallel

- Which _residues_ are paired?

- odd

- even

- There are n!2 n-2 possible
- n-stranded motifs
-    96 motifs for n=4
-  960 motifs for n=5

- It takes weeks to
- create some of these
- configurations using
- constrained local
- minimizations!

*Distribution of Beta Sheets in Proteins with Applications to Structure Prediction*
*Ruckzinski, Kooperberg, Bonneau, and Baker, Proteins 48,2002*

## 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

## 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

## Phase 1 with ProteinShop

- Amino Acid Sequence

- Initial Configurations

- Final Configuration

- Structure Sequence

- Pre-configuration

- Initial Configurations

***ProteinShop***
***takes minutes***

## Slide 15

## Slide 16

## Slide 17

## Slide 18

## Slide 19

## 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

##  Phase 2

- Amino Acid Sequence

- Initial Configurations

- Final Configuration

- Initial Configurations

- Final Configuration

- Takes months to
- converge using
- hundreds of
- processors on
- Seaborg!

##  Phase 2 with ProteinShop

-  Phase 2 with ProteinShop

- Amino Acid Sequence

- Initial Configurations

- Final Configuration

- Initial Configurations

- Final Configuration

- Steering System

- Will reduce
- computation time

## Monitoring System

- Monitor progress of overall optimization/each optimization process

## 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

## Steering System

- Change configurations during optimization to account 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

## 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

## ProteinShop

- O. Kreylos, N. Max, B. Hamann,
- S. Crivelli, and W. Bethel. *Interactive Protein Manipulation*, Winner of the Best Application Award IEEE Visualization 2003, Seattle.

- Available to academic and non-profit organizations
- proteinshop.lbl.gov