Homology Modeling

Lu Chih-Hao

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Why study protein structure?

• Proteins play crucial functional roles in all biological processes: enzymatic catalysis, signaling messengers …

• Function depends on 3D structure.

• Easy to obtain protein sequences, difficult to determine structure.

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Where find the data?

• Protein Data Bank (PDB)– http://www.rcsb.org/pdb/– > ~65,500 structures of proteins

• Text file contain: coordinates for each heavy atom from the first residue to the last

X Y Z

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PDB Statistics

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TIM barrel

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How to determine the protein structure?

• By experimentation– X-Ray– NMR (nuclear magnetic resonance spectroscopy)

• Sequence-Structure gap

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Protein Structure Prediction

• The primary sequence already contain all the information necessary to define 3D structure.

• The 3D protein structure can be predicted according to three main categories of methods (Rost & O’Donoghue, 1997): (1) homology modeling; (2) fold recognition (threading); (3) ab initio techniques.

• Homology modeling is currently the most accurate method to predict protein 3D structure (Tramontano, 1998).

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Protein Structure Prediction

Sequence

Sequence HomologyTo known fold

HomologyModeling

>30%

Threading

Match Found?

Ab initio

No

Model

Yes

<30%

8

.

0

20

40

60

80

100

0 50 100 150 200 250

identity

Number of residues aligned

Perc

enta

ge s

equence

identi

ty/s

imila

rity

(B.Rost, Columbia, NewYork)

Sequence identity implies structural similarity

Sequence similarity implies structural similarity?

Safe zone

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Homology Modeling

• Basis– Structure is much more conserved than sequence

during evolution

• Limited applicability– A large number of proteins and ORFs have no

similarity to proteins with known structure

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??

KQFTKCELSQNLYDIDGYGRIALPELICTMFHTSGYDTQAIVENDESTEYGLFQISNALWCKSSQSPQSRNICDITCDKFLDDDITDDIMCAKKILDIKGIDYWIAHKALCTEKLEQWLCEKE

Use as template

8lyz1alc

KVFGRCELAAAMKRHGLDNYRGYSLGNWVCAAKFESNFNTQATNRNTDGSTDYGILQINSRWWCNDGRTPGSRNLCNIPCSALLSSDITASVNCAKKIVSDGNGMNAWVAWRNRCKGTDVQAWIRGCRLShare Similar

Sequence

Homologous

What is Homology Modeling?

Target Template

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Structure prediction by homology modeling

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Step 1

Step 2

Step 3

Step 4

Homology detection and template selection

• Homology detection– To detect the fold of a probe sequence from a library

of known target fold.

• The three type of sequence based methods:– Pair-wise sequence-sequence comparison

• FASTA, BLAST

– Sequence profile comparison• PSI-BLAST, IMPALA, HMMER, SAM

– Profile-profile comparison• prof_sim, COMPASS

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Q T

Sequence-Sequence comparison

BLAST, FASTA, SSEARCH

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Q T

Profile-Sequence comparison

PSI-BLAST15

PSI-BLAST Overview

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Q T

Sequence-Profile comparison

RPS-BLAST, IMPALA, HMMER, SAM

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Q T

Profile-Profile comparison

prof_sim, COMPASS18

Method_11lmb3 <-> 1pou shift = 9.34 σ = 39.62LEDARRLKAIYEKKKNELGLSQESVADKMGMGQSGVGALFNGINALNAYNAALLAKILKVSVEEFSPSIAREIYEMYEAHHHHHHHHHHHHHHHHHCCCChhhhhhhhccchhhhhhhhccccccchhhhhhhhhhhccchhhcchhhhhhhhhhhhh||||||||||||||||||||| ++++++++ + ++++++++++++ ++++++++000000000000000000000 99999999 X XXXXXXXXXXXX XXXXXXXXHHHHHHHHHHHHHHHHHHCCC---------cchhhhhhhhhcccccc---chhhhhhhcccccccchhhhhhhhhhhhhLEELEQFAKTFKQRRIKLGFT---------QGDVGLAMGKLYGNDFS---QTTISRFEALNLSFKNMCKLKPLLEKWLN

Method_21lmb3 <-> 1pou Shift = 0.67 σ = 60.78LEDARRLKAIYEKKKNELGLS----QESVADKMG--MGQSGVGALFN-GINALNAYNAALLAKILKVSVEEFSHHHHHHHHHHHHHHHHHCCCC----hhhhhhhhc--cCHHHHHHHHC-cccccchhhhhhhhhhhccchhhcc||||||||||||||||||||| ---- |||||||||| -- ++++++++ ++ 000000000000000000000 4444 0000000000 11 11111111 44 HHHHHHHHHHHHHHHHHHCCCcchhhhhhhhhcccccCCHHHHHHHCccccccchhhhhhhhhhh---hhhccLEELEQFAKTFKQRRIKLGFTQGDVGLAMGKLYGNDFSQTTISRFEALNLSFKNMCKLKPLLEKW---LNDAE

The importance of the sequence alignment

SCR; structure conserved region SVR; structure variable region

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Backbone generation

• Rigid-body assembly– Building model core

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Construction of loops might be done by:

Wedemeyer,ScheragaJ. Comput. Chem.20, 819-844(1999)

Ab initio methods - without any prior knowledge. This is done by empirical scoring functions that check large number of conformations and evaluates each of them.

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data clustereddata

library

Construction of loops might be done by:

Using database of loops which appear in known structures. The loops could be categorized by their length or sequence

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Scan database and search protein fragments with correct number of residuesand correct end-to-end distances

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Loop length

cRM

S (Ǻ

)

Method breaksdown for loopslarger than 9

Loop Modeling: A database approach

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GDT_TS = 45.96 GDT_TS = 60.48

Predicted model with long loop Without loop

Target: 2bj7A

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Errors in Homology Modeling

a) Side chain packing b)Distortions and shifts c) No template

Template ModelTrue structure30

Errors in Homology Modeling

d) Misalignments e) Incorrect template

(Marti-Renom et al., 2000)

Template ModelTrue structure31

PROCHECK, Verify3D, Prosa, Anolea, Bala …

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PROCHECK

β

α http://www.biochem.ucl.ac.uk/~roman/procheck/procheck.html

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Verify3D

• Verify3D analyzes the compatibility of an atomic model (3D) with its own amino acid sequence (1D).

Luethy et al., 1992 34

ProQ Server

• ProQ is a neural network-based predictor

– Structural features quality of a protein model.

Arne Elofssons group: http://www.sbc.su.se/~bjorn/ProQ/

Correct Good Very goodLGscore > 1.5 LGscore > 3 LGscore > 5MaxSub > 0.1 MaxSub > 0.5 MaxSub > 0.8

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Modeling accuracy

(Marti-Renom et al., 2000)

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Utility of Structural Information

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(PS)2: protein structure prediction server

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Consensus strategy

• The idea of consensus analysis is to gather predictions from a set of different methods.

• The performance of consensus methods is significantly higher than for individual methods.

3d-shotgun (Fischer D., 2003)3d-jury (Ginalski K et al., 2003)Pmodeller (Bjorn W et al., 2003)

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Structure prediction by homology modeling

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Step 1

Step 2

Step 3

Step 4

Figure 1. Overview of the protein structure prediction server, (PS)2.

Overview of the (PS)2 method

Step1: Template search/selection by the

consensus of PSI-BLAST and IMPALA

Step2: Target-template alignment by the consensus of T-Coffee, PSI-BLAST,

and IMPALA

Step3: Model building by MODELLER and structure evaluation and visualization

by CHIME and Raster3D

(d)

(a)

(b) (c)

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: Aligned path of PSI-BLAST

: Aligned path of T-Coffee

: Aligned path of IMPALA

: Final aligned path

9: aligned in 1st cycle7: aligned in 2nd cycle5: aligned in 3rd cycle3: aligned in 4th cycle4 and 2: unfeasible solution

Input: target and template sequences

Output: target-template aligned sequences

Step 1: Initial all entries of the aligned matrix to 0. Align target and template sequences using PSI-BLAST, IMPALA, and T-Coffee.

Step 2: Sum aligned scores of these three alignments for each position with different scoring weights.

Step 3: Take the positions with the highest score as the aligned points to build the final target-template alignment. (e.g., the highest scoring is 9 for the 1st cycle in (b) )

Step 4: Identify the unfeasible positions. ( 4 and 2 in (b))

Step 5: Change the scores of unfeasible positions and the aligned points to 0.

Step 6: Repeatedly Steps 3 and 5 until all entries are 0.

Step 7: Output the path with the aligned points as the target-template alignment

(b)(a)

Alignment method

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http://predictioncenter.org/

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CASP3 servers registered:

1. 3D-PSSM (Sternberg) sternber@icrf.icnet.uk 2. Karplus karplus@cse.ucsc.edu 3. frsvr (Fischer) dfischer@cs.bgu.ac.il 4. pscan (Eloffson) arne@bimbo.biokemi.su.se 5. BASIC (Godzik) adam@scripps.edu 6. GenTHREADER jones@globin.bio.warwick.ac.uk 7. Valentina di Francesco valedf@tigr.org 8. TOPITS (Rost) Burkhard.Rost@EMBL-Heidelberg.de 9. Bork

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CASP8 servers registered:

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}8 4, 2, 1,{(%)4

100_

dN

GDT

TSGDT d

d

- N is the total number residues of the target (native structure)- GDTd is the number of aligned residues whose Cα-atom distance

between the target and predicted model is less than d- d is 1, 2, 4, or 8 Å.

Model Evaluation

• Performance evaluation– Comparing the 47 CM targets to evaluate the

performance with the other groups in CASP6.

• GDT_TS Score

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10 272

6 294 Native structure

PSI-BLAST modelGDT_TS = 64.97

272(PS)2 modelGDT_TS = 67.22

GDT_TS = 66.00

10

10 272 IMPALA modelGDT_TS = 63.32

294 T-Coffee modelGDT_TS = 65.14

T0264 (1wde)

Aligned rate: 91.00 %

Aligned rate: 91.00 %

Aligned rate: 100 %6

Aligned rate: 100 %6 294

Figure 3. Comparison (PS)2 with PSI-BLAST, IMPALA, and T-Coffee of the prediction accuracies (global / local GDT_TS scores) on target T0264.

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Figure 4. Comparison of (PS)2 models with all automated servers in CASP6.

0

20

40

60

80

100

T0196

T0199_1

T0200

T0204

T0205

T0208

T0211

T0222_1

T0223_1

T0226

T0226_1

T0229

T0229_1

T0229_2

T0231

T0233

T0233_1

T0233_2

T0234

T0235_1

T0240

T0246

T0247

T0247_1

T0247_2

T0247_3

T0264

T0264_1

T0264_2

T0266

T0267

T0268

T0268_1

T0268_2

T0269

T0269_1

T0269_2

T0271

T0274

T0275

T0276

T0277

T0279

T0279_1

T0279_2

T0280_1

T0282

Targets

GD

T_T

S Sc

ore

(%)

50

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Table 1. Compare with the other groups in CASP6

(PS)2 RBTA ESYP 3DJR MGTH 3DJS PROS PMO5 PRCM PCO5 PCOB

Average GDT_TS

65.89 64.92 63.14 62.54 61.27 61.08 58.11 57.93 57.62 56.37 37.57

• Cases

T0269, Template 1prxA(PS)2 model, GDT_TS: 85.76

T0269, Template 1qq2AESYP model, GDT_TS: 78.48

http://ps2.life.nctu.edu.tw

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