Practical session 2bIntroduction to 3D

Modelling and threading9:30am-10:00am

3D modeling and threading10:00am-10:30am

Analysis of mutations in MYH6

Miguel AndradeMax Delbrück Center for Molecular Medicine

Miguel.andrade@mdc-berlin.de

IntroductionProtein tertiary structure

Secondary structure elements fold together

IntroductionProtein quaternary structure

Folded proteins form a complex

Protein domains are structural units (average 160 aa) that share:

FunctionFoldingEvolution

Proteins normally are multidomain (average 300 aa)

Introduction

Protein domains are structural units (average 160 aa) that share:

FunctionFoldingEvolution

Proteins normally are multidomain (average 300 aa)

Introduction

X-ray crystallography (70,714 in PDB)• need crystals

Nuclear Magnetic Resonance (NMR) (9,312)• proteins in solution• lower size limit (600 aa)

Electron microscopy (422)• Low resolution (>5A)

Determination of protein structure

Determination of protein structure

resolution 2.4 A

Determination of protein structure

resolution 2.4 A

Structural genomics

Currently: 81K 3D structures from around 27K seqs16M sequences in UniProt

only 0.17%!

Structural genomics

Currently: 81K 3D structures from around 27K seqs16M sequences in UniProt

50% sequences covered (25% in 1995)

only 0.17%!

Strategy for analysisQuery Sequence

Yes

3D Modeling by homology

No

2D Prediction3D Ab initio3D Threading

Similar to PDBsequence?

Predict domainsCut

3D structure predictionApproaches

Class 1

Comparative modeling

Class 2

Ab initio

Need sequence only

Need similarity to a known structure

Threading

3D structure predictionApproaches

Search for sequences of known structure similar to target

Comparative modeling (30% to 50% id)

Model from template core regions and from loops and side chains of structures that might be unrelated

Atom coordinates from conserved residues

Optimize distance constraints derived from sequence-template alignment

Extra methods for loops, turns, and side chains

3D structure predictionApproaches

Thread target sequence through a library of known folds.

Select right fold based on energy considerations

More computational cost – but detect more distant relationships

Threading (identity can be lower than 30%)

3D structure predictionApproaches

Explore conformational space

Limit the number of atoms

Break the problem into fragments of sequence

Optimize hydrophobic residue burial and pairing of beta-strands

Limited success

Ab initio

Relation between sequence identity and accuracy/applications

From:Baker and Sali (2001) Science

3D structure predictionApplications: target design

Query sequence

catalytic center

known 3D

LeuGly

model 3D by homology

Gly Lys+

similar toL G

G K

3D structure predictionApplications: fit to low res 3D

Query sequence 1

low resolution 3D (electron microscopy)

Query sequence 2

3D structure predictionGenTHREADER

David Jones http://bioinf.cs.ucl.ac.uk/psipred/

Input sequence

Relatively quick, 5 minutes

GenTHREADER Jones (1999) J Mol Biol

Output GenTHREADER

3D structure predictionGenTHREADER

3D structure predictionPhyre

http://www.sbg.bio.ic.ac.uk/phyre2/

Kelley et al (2000) J Mol BiolKelley and Sternberg (2009) Nature Protocols

3D structure predictionI-Tasser

Jeffrey Skolnick TasserYang Zhang I-Tasser

Lee and Skolnick (2008) Biophysical JournalRoy et al (2010) Nature Methods

ThreadingFold 66% sequences <200 aa long of low homology to PDB

Just submit your sequence and wait… (some days)

Output are predicted structures (PDB format)

3D structure predictionI-Tasser

Roy et al (2010) Nature Methods

3D structure predictionI-Tasser

http://zhanglab.ccmb.med.umich.edu/I-TASSER/

3D structure predictionI-Tasser

3D structure predictionQUARK

http://zhanglab.ccmb.med.umich.edu/QUARK/

3D structure predictionMODbase

Andrej Sali http://modbase.compbio.ucsf.edu/

Pieper et al (2011) Nucleic Acids Research

3D structure predictionMODbase