1. Protein Structure Prediction
Lab 3 - BLAST
BCB 444/544
9/6/07
Lab 7
Protein Structure Prediction
Oct 11, 2007
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

2. Chp 14 - Secondary Structure Prediction
Lab 3 - BLAST
9/6/07
Chp 14 - Secondary Structure Prediction
SECTION V STRUCTURAL BIOINFORMATICS
Xiong: Chp 14
Protein Secondary Structure Prediction
Secondary Structure Prediction for Globular Proteins
Secondary Structure Prediction for Transmembrane Proteins
Coiled-Coil Prediction
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

3. Secondary Structure Prediction
Lab 3 - BLAST
9/6/07
Secondary Structure Prediction
Has become highly accurate in recent years (>85%)
Usually 3 (or 4) state predictions:
H = -helix
E = -strand
C = coil (or loop)
(T = turn)
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

4. Secondary Structure Prediction Methods
Lab 3 - BLAST
9/6/07
Secondary Structure Prediction Methods
1st Generation methods
Ab initio - used relatively small dataset of structures available
Chou-Fasman - based on amino acid propensities (3-state)
GOR - also propensity-based (4-state)
2nd Generation methods
based on much larger datasets of structures now available
GOR II, III, IV, SOPM, GOR V, FDM
3rd Generation methods
Homology-based & Neural network based
PHD, PSIPRED, SSPRO, PROF, HMMSTR, CDM
Meta-Servers
combine several different methods
Consensus & Ensemble based
JPRED, PredictProtein, Proteus
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

5. Secondary Structure Prediction Servers
Lab 3 - BLAST
9/6/07
Secondary Structure Prediction Servers
Prediction Evaluation?
Q3 score - % of residues correctly predicted (3-state)
in cross-validation experiments
Best results? Meta-servers
(scroll for 2' structure prediction)
JPred
PredictProtein Rost, Columbia
Best "individual" programs? ??
CDM Sen…Jernigan, ISU
FDM (not available separately as server) Cheng…Jernigan, ISU
GOR V Kloczkowsky…Jernigan, ISU
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

6. Consensus Data Mining (CDM)
Lab 3 - BLAST
Consensus Data Mining (CDM)
9/6/07
Developed by Jernigan Group at ISU
Basic premise: combination of 2 complementary methods can enhance performance by harnessing distinct advantages of both methods; combines FDM & GOR V:
FDM - Fragment Data Mining - exploits availability of sequence-similar fragments in the PDB, which can lead to highly accurate prediction - much better than GOR V - for such fragments, but such fragments are not available for many cases
GOR V - Garnier, Osguthorpe, Robson V - predicts secondary structure of less similar fragments with good performance; these are protein fragments for which FDM method cannot find suitable structures
For references & additional details:
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

7. BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
9/6/07
Secondary Structure Prediction: for Different Types of Proteins/Domains
For Complete proteins:
Globular Proteins - use methods previously described
Transmembrane (TMM) Proteins - use special methods
(next slides)
For Structural Domains: many under development:
Coiled-Coil Domains (Protein interaction domains)
Zinc Finger Domains (DNA binding domains),
others…
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

8. SS Prediction for Transmembrane Proteins
Lab 3 - BLAST
SS Prediction for Transmembrane Proteins
9/6/07
Transmembrane (TM) Proteins
Only a few in the PDB - but ~ 30% of cellular proteins are membrane-associated !
Hard to determine experimentally, so prediction important
TM domains are relatively 'easy' to predict!
Why? constraints due to hydrophobic environment
2 main classes of TM proteins:
- helical
- barrel
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

9. SS Prediction for TM -Helices
Lab 3 - BLAST
SS Prediction for TM -Helices
9/6/07
-Helical TM domains:
Helices are amino acids long (span the membrane)
Predominantly hydrophobic residues
Helices oriented perpendicular to membrane
Orientation can be predicted using "positive inside" rule
Residues at cytosolic (inside or cytoplasmic) side of TM helix, near hydrophobic anchor are more positively charged than those on lumenal (inside an organelle in eukaryotes) or periplasmic side (space between inner & outer membrane in gram-negative bacteria)
Alternating polar & hydrophobic residues provide clues to interactions among helices within membrane
Servers?
TMHMM or HMMTOP - 70% accuracy - confused by hydrophobic signal peptides (short hydrophobic sequences that target proteins to the endoplasmic reticulum, ER)
Phobius - 94% accuracy - uses distinct HMM models for TM helices
& signal peptide sequences
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

10. SS Prediction for TM -Barrels 
Lab 3 - BLAST
SS Prediction for TM -Barrels 
9/6/07
-Barrel TM domains: 
-strands are amphipathic (partly hydrophobic, partly hydrophilic)
Strands are amino acids long
Every 2nd residue is hydrophobic, facing lipid bilayer
Other residues are hydrophilic, facing "pore" or opening
Servers? Harder problem, fewer servers…
TBBPred - uses NN or SVM (more on these ML methods later)
Accuracy ?
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

11. Chp 15 - Tertiary Structure Prediction
Lab 3 - BLAST
9/6/07
Chp 15 - Tertiary Structure Prediction
SECTION V STRUCTURAL BIOINFORMATICS
Xiong: Chp 15
Protein Tertiary Structure Prediction
Methods
Homology Modeling
Threading and Fold Recognition
Ab Initio Protein Structural Prediction
CASP
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

12. Protein Tertiary Structure Prediction
Lab 3 - BLAST
9/6/07
Protein Tertiary Structure Prediction
3 Major Methods:
Homology Modeling (easiest!)
Threading and Fold Recognition (harder)
Ab Initio Protein Structural Prediction (really hard)
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

13. BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
Comparative Modeling?
9/6/07
Comparative modeling - term is sometimes used interchangeably with homology modeling, but also sometimes used to mean both homology modeling and/or threading/fold recognition
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

14. Provides both folding pathway & folded structure
Lab 3 - BLAST
9/6/07
Ab Initio Prediction
Develop energy function
bond energy
bond angle energy
dihedral angle energy
van der Waals energy
electrostatic energy
Calculate structure by minimizing energy function
(usually Molecular Dynamics or Monte Carlo methods)
Ab initio prediction - impractical for most real (long) proteins
Computationally? very expensive
Accuracy? Usually poor for all except short peptides
(but much improvement recently!)
Provides both folding pathway & folded structure
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

15. Provide folded structure only
Lab 3 - BLAST
9/6/07
Comparative Modeling
Two types:
1) Homology modeling
2) Threading (fold recognition)
Both rely on availability of experimentally determined structures that are "homologous" or at least structurally very similar to target
Provide folded structure only
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

16. BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
9/6/07
Homology Modeling
Identify homologous protein sequences (-BLAST)
Among available structures (in PDB), choose one with closest sequence to target as template
(can combine steps 1 & 2 by using PDB-BLAST)
Build model by placing target sequence residues in corresponding positions of homologous structure & refine by "tweaking" modeled structure (energy minimization)
Homology modeling - works "well"
Computationally? "relatively" inexpensive
Accuracy? higher sequence identity  better model
Requires ~30% sequence identity with sequence for which structure is known
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

17. Threading - Fold Recognition
Lab 3 - BLAST
9/6/07
Threading - Fold Recognition
Identify “best” fit between target sequence & template structure
Develop energy function
Develop template library
Align target sequence with each template & score
Identify top scoring template (1D to 3D alignment)
Refine structure as in homology modeling
Threading - works "sometimes"
Computationally? Can be expensive or cheap, depends on energy function & whether "all atom" or "backbone only" threading
Accuracy? in theory, should not depend on sequence identity (should depend on quality of template library & "luck")
Usually, higher sequence identity to protein of known structure  better model
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs

18. BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
Today's Lab:
9/6/07
Homology Modeling - using SWISS-MODEL
Threading - using 3-D JURY (BioinfoBank, a METAserver)
Take a look at CASP contest:
CASP7 contest in 2006
BCB 444/544 F07 ISU Dobbs - Lab 3 - BLAST
BCB 444/544 Fall 07 Dobbs