Difference between revisions of "Homology based structure predictions BCKDHA"

From Bioinformatikpedia
(iTasser)
(iTasser)
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Sequ GVKTFQFPFAEQLEKVAEQFPTFQILNEEGEVVNEEAMPELSDEQLKELMRRMVYTRILDQRSISLNRQGRLGFYAPTAGQEASQIASHFALEKEDFILP<br>
 
Sequ GVKTFQFPFAEQLEKVAEQFPTFQILNEEGEVVNEEAMPELSDEQLKELMRRMVYTRILDQRSISLNRQGRLGFYAPTAGQEASQIASHFALEKEDFILP<br>
  +
Pred cccccccccHHHcccccccccSSSSSccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHccccccccccccHHHHHHHHHHHcccccSSSc<br>
Pred CCCCCCCCCHHHCCCCCCCCCSSSSSCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCHHHHHHHHHHHCCCCCSSSC<br>
 
 
Conf 9988678803312122677876989899998888756799999999999999999999999999999678854562888879999999986799898980
 
Conf 9988678803312122677876989899998888756799999999999999999999999999999678854562888879999999986799898980
   
 
Sequ GYRDVPQIIWHGLPLYQAFLFSRGHFHGNQIPEGVNVLPPQIIIGAQYIQAAGVALGLKMRGKKAVAITYTGDGGTSQGDFYEGINFAGAFKAPAIFVVQ<br>
 
Sequ GYRDVPQIIWHGLPLYQAFLFSRGHFHGNQIPEGVNVLPPQIIIGAQYIQAAGVALGLKMRGKKAVAITYTGDGGTSQGDFYEGINFAGAFKAPAIFVVQ<br>
  +
Pred ccHHHHHHHHccccHHHHHHHHcccccccccccccccccccccHHccHHHHHHHHHHHHHcccccSSSSSScccccccHHHHHHHHHHHHHcccSSSSSS<br>
Pred CCHHHHHHHHCCCCHHHHHHHHCCCCCCCCCCCCCCCCCCCCCHHCCHHHHHHHHHHHHHCCCCCSSSSSSCCCCCCCHHHHHHHHHHHHHCCCSSSSSS<br>
 
 
Conf 6226899998699899999973687767878999865377730415555899999999964989889999347621101599999999996799899982
 
Conf 6226899998699899999973687767878999865377730415555899999999964989889999347621101599999999996799899982
   
 
Sequ NNRFAISTPVEKQTVAKTLAQKAVAAGIPGIQVDGMDPLAVYAAVKAARERAINGEGPTLIETLCFRYGPHTMSGDDPTRYRSKELENEWAKKDPLVRFR<br>
 
Sequ NNRFAISTPVEKQTVAKTLAQKAVAAGIPGIQVDGMDPLAVYAAVKAARERAINGEGPTLIETLCFRYGPHTMSGDDPTRYRSKELENEWAKKDPLVRFR<br>
  +
Pred cccSSccccHHHHHccccHHHHHHcccccSSSSccccHHHHHHHHHHHHHHHHcccccSSSSSSSSSScccccccccccccccHHHHHHHHHcccHHHHH<br>
Pred CCCSSCCCCHHHHHCCCCHHHHHHCCCCCSSSSCCCCHHHHHHHHHHHHHHHHCCCCCSSSSSSSSSSCCCCCCCCCCCCCCCHHHHHHHHHCCCHHHHH<br>
 
 
Conf 7972403229877479878986221799858987957999999999999999828998899999976158657889975678999999988379099999
 
Conf 7972403229877479878986221799858987957999999999999999828998899999976158657889975678999999988379099999
   
 
Sequ KFLEAKGLWSEEEENNVIEQAKEEIKEAIKKADETPKQKVTDLISIMFEELPFNLKEQYEIYKEKESK<br>
 
Sequ KFLEAKGLWSEEEENNVIEQAKEEIKEAIKKADETPKQKVTDLISIMFEELPFNLKEQYEIYKEKESK<br>
  +
Pred HHHHHcccccHHHHHHHHHHHHHHHHHHHHHHHHcccccHHHHHHHHcccccHHHHHHHHHHHHHHcc<br>
Pred HHHHHCCCCCHHHHHHHHHHHHHHHHHHHHHHHHCCCCCHHHHHHHHCCCCCHHHHHHHHHHHHHHCC<br>
 
 
Conf 99998799999999999999999999999999858998999998451038998799999999998549
 
Conf 99998799999999999999999999999999858998999998451038998799999999998549
 
</tt>
 
</tt>

Revision as of 14:59, 7 June 2011

1.Calculation of models

To find similar structures to BCKDHA we ran HHsearch:
hhsearch -i query -d database -o output

It found the following 10 hits in the pdb70 database.

No Hit Prob E-value P-value Score SS Cols Query HMM Template HMM Identity
1 2bfd_A 2-oxoisovalerate dehydr 1.0 1 1 791.3 0.0 400 1-400 1-400 (400) 99%
2 1qs0_A 2-oxoisovalerate dehydr 1.0 1 1 571.5 0.0 349 32-382 52-407 (407) 39%
3 1w85_A Pyruvate dehydrogenase 1.0 1 1 530.8 0.0 356 8-382 6-362 (368) 34%
4 1umd_A E1-alpha, 2-OXO acid de 1.0 1 1 521.8 0.0 351 34-386 16-367 (367) 37%
5 2ozl_A PDHE1-A type I, pyruvat 1.0 1 1 482.7 0.0 331 46-380 25-356 (365) 27%
6 3l84_A Transketolase; TKT, str 1.0 1 1 85.4 0.0 133 161-297 113-252 (632) 21%
7 2r8o_A Transketolase 1, TK 1; 1.0 1 1 74.5 0.0 121 161-285 113-245 (669) 33%
8 2o1x_A 1-deoxy-D-xylulose-5-ph 1.0 1 1 74.2 0.0 127 161-287 122-254 (629) 18%
9 1gpu_A Transketolase; transfer 1.0 1 1 74.2 0.0 140 161-302 115-265 (680) 22%
10 3m49_A Transketolase; alpha-be 1.0 1 1 68.8 0.0 121 161-285 139-271 (690) 31%

> 60% sequence identity:
-1w85_A
> 40% sequence identity:
< 40% sequence identity (ideally go towards 20%) :
-1qs0_A, 1umd_A, 1w85_A, 2r8o_A, 3m49_A, 2ozl_A, 1gpu_A, 3l84_A, 2o1x_A

HHSearch has only hits with an identity higher than 60% or lower than 40%.

These are the templates we will work with:
> 60% sequence identity:
-1w85_A -> P21873
< 40% sequence identity (ideally go towards 20%) :
-2r8o_A -> P27302


Modeller

MODELLER is used for homology or comparative modeling of protein three-dimensional structures.It calculates a model containing all non-hydrogen atoms. There are also many other tasks provided by MODELLER like de novo modeling of loops in protein structures, optimization of various models of protein structure with respect to a flexibly defined objective function, multiple alignment of protein sequences and/or structures, clustering, searching of sequence databases, comparison of protein structures, etc.[1]

A tutorial is provided on [2] and on [3]

Protocol Modeller

SWISS-MODEL

SWISS-MODEL server page


To find protein structure homology models SWISS-MODEL can be used. As input it needs a protein sequence or a UniProt AC Code. Optional the template PDB-Id and the chain or a template file can be assigned. SWISS-MODEL is a fully automated protein structure homology-modeling server. It is accessible via the ExPASy web server, or from the program DeepView (Swiss Pdb-Viewer).
SWISS-MODEL

SWISS-MODEL server:

ID link
1w85_A 1w85_A
2r8o_A 2r8o_A

iTasser

1w85_A
1w85_A


Prediction for 1w85_A

Sequ GVKTFQFPFAEQLEKVAEQFPTFQILNEEGEVVNEEAMPELSDEQLKELMRRMVYTRILDQRSISLNRQGRLGFYAPTAGQEASQIASHFALEKEDFILP
Pred cccccccccHHHcccccccccSSSSSccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHccccccccccccHHHHHHHHHHHcccccSSSc
Conf 9988678803312122677876989899998888756799999999999999999999999999999678854562888879999999986799898980

Sequ GYRDVPQIIWHGLPLYQAFLFSRGHFHGNQIPEGVNVLPPQIIIGAQYIQAAGVALGLKMRGKKAVAITYTGDGGTSQGDFYEGINFAGAFKAPAIFVVQ
Pred ccHHHHHHHHccccHHHHHHHHcccccccccccccccccccccHHccHHHHHHHHHHHHHcccccSSSSSScccccccHHHHHHHHHHHHHcccSSSSSS
Conf 6226899998699899999973687767878999865377730415555899999999964989889999347621101599999999996799899982

Sequ NNRFAISTPVEKQTVAKTLAQKAVAAGIPGIQVDGMDPLAVYAAVKAARERAINGEGPTLIETLCFRYGPHTMSGDDPTRYRSKELENEWAKKDPLVRFR
Pred cccSSccccHHHHHccccHHHHHHcccccSSSSccccHHHHHHHHHHHHHHHHcccccSSSSSSSSSScccccccccccccccHHHHHHHHHcccHHHHH
Conf 7972403229877479878986221799858987957999999999999999828998899999976158657889975678999999988379099999

Sequ KFLEAKGLWSEEEENNVIEQAKEEIKEAIKKADETPKQKVTDLISIMFEELPFNLKEQYEIYKEKESK
Pred HHHHHcccccHHHHHHHHHHHHHHHHHHHHHHHHcccccHHHHHHHHcccccHHHHHHHHHHHHHHcc
Conf 99998799999999999999999999999999858998999998451038998799999999998549

2.Evaluation of models

Swissmodel

Numeric evaluation

QMEAN4 global scores

QMEANscore4

1w85_A 2r8o_A
0.596 0.271


QMEAN Z-Score

1w85_A 2r8o_A
-2.872 -6.943
Z-Score plot1 1w85_A
Z-Score plot1 2r8o_A
Z-Score plot2 1w85_A
Z-Score plot2 2r8o_A


Score components

1w85_A 2r8o_A
score components 1w85_A
score components 2r8o_A


Local scores

1w85_A 2r8o_A
Coloring by residue error 1w85_A
Coloring by residue error 2r8o_A
Residue error plot 1w85_A
Residue error plot 2r8o_A


Global scores: QMEAN4:

1w85_A 2r8o_A
Scoring function term Raw score Z-score Raw score Z-score
C_beta interaction energy -152.10 0.11 -47.91 -1.49
All-atom pairwise energy -9145.04 -0.55 -2558.65 -1.98
Solvation energy -14.56 -2.14 10.53 -4.08
Torsion angle energy -57.90 -2.03 18.95 -4.99
QMEAN4 score 0.596 -2.87 0.271 -6.94


Local Model Quality Estimation

1w85_A 2r8o_A
Local Model Quality Estimation 1w85_A
Local Model Quality Estimation 2r8o_A

iTasser

Numeric evaluation