Applied Bioinformatics

Week 12

Bioinformatics & Functional Proteomics

• How to classify proteins into functional classes?• How to compare one proteome with another?• How to include functional/activity/pathway

information in databases?• How to extract functional motifs from sequence

data?• How to predict phenotype from proteotype?

Bioinformatics & Expressional Proteomics

• How to correlate changes in protein expression with disease?

• How to distinguish important from unimportant changes in expression?

• How to compare, archive, retrieve gel data?• How to rapidly, accurately identify proteins from

MS and 2D gel data?• How to include expression info in databases?

Bioinformatics & Structural Proteomics

• How to predict 3D structure from 1D sequence?• How to determine function from structure?• How to classify proteins on basis of structure?• How to recognize 3D motifs and patterns?• How to use bioinformatics databases to help in 3D

structure determination?• How to predict which proteins will express well or

produce stable, folded molecules?

Protein Folding ProblemProtein Folding Problem

“Predict a three-dimensional structure of a protein from its amino acid sequence.”

“How does a protein fold into the structure?”

This question has not been solved for more than half a

century.

Proteins Can Fold into 3D Proteins Can Fold into 3D Structures Spontaneously Structures Spontaneously

The three-dimensional structure of a protein is self-organized in solution.

If we can calculate the energy of the system precisely, it is possible to predict the structure of the protein!

The structure corresponds to the state with the lowest free energy of the protein-solvent system. (Anfinsen’s dogma)

Levinthal ParadoxLevinthal ParadoxWe assume that there are three conformations for each amino acid (ex.

α-helix, β-sheet and random coil). If a protein is made up of 100 amino acid residues, a total number of conformations is

3100 = 515377520732011331036461129765621272702107522001≒ 5 x 1047.

If 100 psec (10-10 sec) were required to convert from a conformation to another one, a random search of all conformations would require

5 x 1047 x 10-10 sec ≒ 1.6 x 1030 years.

However, folding of proteins takes place in msec to sec order. Therefore, proteins fold not via a random search but a more sophisticated search process.

We want to watch the folding process of a protein using molecular simulation techniques.

Why is the Why is the ““Protein FoldingProtein Folding”” so so Important?Important?

• Proteins play important roles in living organisms.• Some proteins are deeply related with diseases. And structural information of

a protein is necessary to explain and predict its gene function as well as to design molecules that bind to the protein in drug design.

• Today, whole genome sequences (the complete set of genes) of various organisms have been deciphered and we realize that functions of many genes are unknown and some are related with diseases.

• Therefore, understanding of protein folding helps us to investigate the functions of these genes and to design useful drugs against the diseases efficiently.

• In addition to that, the understanding opens the door to designing of proteins having novel functions as new nano machines.

Forces Involved in the Protein Forces Involved in the Protein FoldingFolding

• Electrostatic interactions

• van der Waals interactions

• Hydrogen bonds

• Hydrophobic interactions

bonds angles torsions ji ij

ji

ij

ij

ij

ijneqeqrPair R

qq

R

B

R

An

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612

22 )cos(12

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The Energy Function

• Calculate energies for each particle

• Since long range interactions important for each pair of particles the pair-wise interactions should be calculated

System for System for Folding Folding SimulationsSimulations

Without water molecules With water molecules

# of atoms: 304

# of atoms: 304 + 7,377 = 7,681

Much Faster, Much Larger!Much Faster, Much Larger!

• Special-purpose computer– Calculation of non-bonded interactions is performed using the

special chip that is developed only for this purpose. – For example;

• MDM (Molecular Dynamics Machine) or MD-Grape: RIKEN• MD Engine: Taisho Pharmaceutical Co., and Fuji Xerox Co.

• Parallelization– A single job is divided into several smaller ones and they are

calculated on multi CPUs simultaneously. – Today, almost all MD programs for biomolecular simulations

(ex. AMBER, CHARMm, GROMOS, NAMD, MARBLE, etc) can run on parallel computers.

• Fold@Home

Homology Modeling

• Template Selection and Fold Assignment

• Target – Template Alignment

• Model Building– Loop Modeling

– Sidechain Modeling

• Model Evaluation

Fold Assignment and Template Selection

• Identify all protein structures with sequences related to the target, then select templates

• 3 main classes of comparison methods– Compare the target sequence with each database

sequence independently, pair-wise sequence – sequence comparison, BLAST and FASTA

– Multiple sequence comparisons to improve sensitivity, PSI-BLAST

– Threading or 3-D template matching methods

Target – Template Alignment

• Most important step in Homology Modeling• A specialized method should be used for

alignment– Over 40% identity the alignment is likely to be correct. – Regions of low local sequence similarity become

common when overall sequence identity is under 40%. (Saqi et al., Protein Eng. 1999)

– The alignment becomes difficult below 30% sequence identity. (Rost, Protein Eng. 1999)

Model Building

• Construct a 3-D model of the target sequence based on its alignment on template structures

• Three different model building approaches– Modeling by rigid body assembly– Modeling by segment matching– Modeling by satisfaction of spatial restraints

• Accuracies of these models are similar• Template selection and alignment have larger

impact on the model

Swiss-MOD Web Server

Screenshots from the Homology Modeling Server Swiss-Model

• Construct a framework using known protein structures

• Generate the location of the target amino acids on the framework

• If loop regions not determined, additional database search or short simulations

Procedure of the MODELLER program

• After obtaining restraints run a geometry optimization or real-space optimization to satisfy them

Errors in Homology Models

a. Errors in side chain packing

b. Distortions and shifts in correctly aligned regions

c. Errors in regions without a template

d. Errors due to misalignment

e. Incorrect templates

Model Building Programs COMPOSER P www-cryst.bioc.cam.ac.uk

 CONGEN P www.congenomics.com/congen/congen.html

 CPH models S www.cbs.dtu.dk/services/CPHmodels/

 DRAGON Pwww.nimr.mrc.ac.uk/~mathbio/a-aszodi/

dragon.html

 ICM P www.molsoft.com

 InsightII P www.msi.com

 MODELLER P guitar.rockefeller.edu/modeller/modeller.html

 LOOK P www.mag.com

 QUANTA P www.msi.com

 SYBYL P www.tripos.com

 SCWRL P www.cmpharm.ucsf.edu/~bower/scrwl/scrwl.html

 SWISS-MOD S www.expasy.ch/swissmod

 WHAT IF P www.sander.embl-heidelberg.de/whatif/

Applications

End Theory

• Mind mapping

• 10 min break

Practice

3D Structure Prediction?• Get a protein sequence

• Go to: http://bioinf.cs.ucl.ac.uk/psipred– Use threading

• Got to: http://www.rcsb.org/pdb– Find known structure

• Folding@home– Ab inito prediction

• FoldIt (http://fold.it/portal/)Crystal structure of a monomeric retroviral protease solved by protein folding game players.

Increased Diels-Alderase activity through backbone remodeling guided by Foldit players.