Protein Tertiary Structure Prediction

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Protein Tertiary Structure Prediction
Structural Bioinformatics
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The Different levels of Protein Structure
Primary amino acid linear sequence.
Secondary ?-helices, ß-sheets and loops.
Tertiary the 3D shape of the fully folded
polypeptide chain
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Predicting 3D Structure
Outstanding difficult problem

• Comparative modeling (homology)
• Based on structural homology
• Fold recognition (threading)

Based on sequence homology
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Comparative Modeling
Based on Sequence homology
Similar sequences suggests similar structure
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Sequence and Structure alignments of two Retinol
Binding Protein
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Structure Alignments
There are many different algorithms for
structural Alignment.
The outputs of a structural alignment are a
superposition of the atomic coordinates and a
minimal Root Mean Square Distance (RMSD) between
the structures. The RMSD of two aligned
structures indicates their divergence from one
another.
Low values of RMSD mean similar structures
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Comparative Modeling
Based on Sequence homology
Similar sequence suggests similar structure

• Builds a protein structure model based on its
  alignment to one or more related protein
  structures in the database

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Comparative Modeling
Based on Sequence homology

• Accuracy of the comparative model is related to
  the sequence identity on which it is based
• gt50 sequence identity high accuracy
• 30-50 sequence identity 90 modeled
• lt30 sequence identity low accuracy (many
  errors)

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Homology Threshold for Different Alignment
Lengths
Homology Threshold (t)
Alignment length (L)
A sequence alignment between two proteins is
considered to imply structural homology if the
sequence identity is equal to or above the
homology threshold t in a sequence region of a
given length L.
The threshold values t(L) are derived from PDB
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Comparative Modeling

• Similarity particularly high in core
• Alpha helices and beta sheets preserved
• Even near-identical sequences vary in loops

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Comparative Modeling Methods
Based on Sequence homology
MODELLER (Sali Rockefeller/UCSF)
SCWRL (Dunbrack- UCSF )
SWISS-MODEL http//swissmodel.expasy.org//SWISS-M
ODEL.html
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Comparative Modeling
Based on Sequence homology
Modeling of a sequence based on known
structures Consist of four major steps

1. Finding a known structure(s) related to the
   sequence to be modeled (template), using sequence
   comparison methods such as PSI-BLAST

2. Aligning sequence with the templates
3. Building a model
4. Assessing the model
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Fold Recognition
Based on Structure homology
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Based on Secondary Structure
Protein Folds sequential and spatial arrangement
of secondary structures
Hemoglobin
TIM
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Similar folds usually mean similar function
Transcription factors
Homeodomain
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The same fold can have multiple functions
Rossmann
12 functions
31 functions
TIM barrel
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Fold Recognition
Based on Structure homology

• Methods of protein fold recognition attempt to
  detect similarities between protein 3D structure
  that have no significant sequence similarity.
• Search for folds that are compatible with a
  particular sequence.
• "the turn the protein folding problem on it's
  head rather than predicting how a sequence will
  fold, they predict how well a fold will fit a
  sequence

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Based on Structure homology
Basic steps in Fold Recognition Compare
sequence against a Library of all known Protein
Folds (finite number)
Query sequence
MTYGFRIPLNCERWGHKLSTVILKRP...
Goal find to what folding template the sequence
fits best
There are different ways to evaluate
sequence-structure fit
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Based on Secondary Structure homology
There are different ways to evaluate
sequence-structure fit
1) ... 56) ... n)
...
...
MAHFPGFGQSLLFGYPVYVFGD...
-10 ... -123 ... 20.5
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Programs for fold recognition
Based on Secondary Structure homology

• TOPITS (Rost 1995)
• GenTHREADER (Jones 1999)
• SAMT02 (UCSC HMM)
• 3D-PSSM http//www.sbg.bio.ic.ac.uk/3dpssm/

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Ab Initio Modeling

• Compute molecular structure from laws of physics
  and chemistry alone
• Theoretically Ideal solution
• Practically nearly impossible
• WHY ?
• Exceptionally complex calculations
• Biophysics understanding incomplete

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Ab Initio Methods

• Rosetta (Bakers lab, Seattle)
• Undertaker (Karplus, UCSC)

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CASP - Critical Assessment of Structure Prediction

• Competition among different groups for resolving
  the 3D structure of proteins that are about to be
  solved experimentally.
• Current state -
• ab-initio - the worst, but greatly improved in
  the last years.
• Modeling - performs very well when homologous
  sequences with known structures exist.
• Fold recognition - performs well.

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What can you do?FOLDITSolve Puzzles for Science

• A computer game to fold proteins
• http//fold.it/portal/puzzles

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Whats Next

• Predicting function from structure

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Structural Genomics a large scale structure
determination project designed to cover all
representative protein structures
ATP binding domain of protein MJ0577
Zarembinski, et al., Proc.Nat.Acad.Sci.USA,
9915189 (1998)
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As a result of the Structure Genomic initiative
many structures of proteins with unknown
function will be solved
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Approaches for predicting function from structure
ConSurf - Mapping the evolution conservation
on the protein structure
http//consurf.tau.ac.il/
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Approaches for predicting function from structure
PFPlus Identifying positive electrostatic
patches on the protein structure
http//pfp.technion.ac.il/
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A method to distinguish DNA from RNA-binding
proteins
DNA binding interface
RNA binding interface
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RNA and DNA binding interfaces tend to have
different geometric features
DNA binding interface
RNA binding interface
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Applying Differential Geometry to characterize
DNA and RNA binding proteins
k1 - minimal curvature
K2- MAXIMAL CURVATURE
H(k1k2)/2 Mean Curvature Kk1k2 Gaussian
Curvature
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Applying Differential Geometry to characterize
DNA and RNA proteins
Flat
Peak
Pit
Minimal Surface
Saddle ridge
Ridge
Valley
Saddle valley
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Applying Differential Geometry for DNA and RNA
function prediction
Frequency of points
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RNA binding surfaces are distinguished from DNA
binding surfaces based on Differential Geometric
features
76 RNA-binding
78 DNA binding
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Differential Geometry can correctly
determine whether a given binding domain binds
RNA or DNA
Frequency of points
RNA pattern
DNA pattern
Shazman et al, NAR 2011
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How can we view the protein structure ?

• Download the coordinates of the structure from
  the PDB
• http//www.rcsb.org/pdb/
• Launch a 3D viewer program
• For example we will use the program Pymol
• The program can be downloaded freely from
• the Pymol homepage http//pymol.org
• Upload the coordinates to the viewer

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Pymol example

• Launch Pymol
• Open file 1aqb (PDB coordinate file)
• Display sequence
• Hide everything
• Show main chain / hide main chain
• Show cartoon
• Color by ss
• Color red
• Color green, resi 140

Help http//pymol.org