Difference between revisions of "Homology based structure predictions BCKDHA"
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To run modeller with more than one target we use the targets:<br> |
To run modeller with more than one target we use the targets:<br> |
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+ | -1dtw:A 95%<br> |
| − | - |
+ | -2bfe:A 94%<br> |
| − | - |
+ | -2bfb:A 99%<br> |
-2bfd:A 99%<br> |
-2bfd:A 99%<br> |
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-3m49:A 31%<br> |
-3m49:A 31%<br> |
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Revision as of 22:00, 7 June 2011
Contents
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:
-2bfd_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, -1w85_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:
-2bfd_A
< 40% sequence identity (ideally go towards 20%) :
-2r8o_A
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]
To run modeller with more than one target we use the targets:
-1dtw:A 95%
-2bfe:A 94%
-2bfb:A 99%
-2bfd:A 99%
-3m49:A 31%
-1gpu:A 22%
-2o1x:A 18%
SWISS-MODEL
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 |
|---|---|
| 2bfd_A | 2bfd_A |
| 2r8o_A | 2r8o_A |
Prediction for 2bfd_A
TARGET 51 KPQFPGAS AEFIDKLEFI QPNVISGIPI YRVMDRQGQI INPSEDPHLP
2bfdA 6 kpqfpgas aefidklefi qpnvisgipi yrvmdrqgqi inpsedphlp
TARGET sss ss s
2bfdA sss ss s
TARGET 99 KEKVLKLYKS MTLLNTMDRI LYESQRQGRI SFYMTNYGEE GTHVGSAAAL
2bfdA 54 kekvlklyks mtllntmdri lyesqrqgri sfymtnygee gthvgsaaal
TARGET hhhhhhhhhh hhhhhhhhhh hhhhhhh h hhhhhhhh
2bfdA hhhhhhhhhh hhhhhhhhhh hhhhhhh h hhhhhhhh
TARGET 149 DNTDLVFGQY REAGVLMYRD YPLELFMAQC YGNISDLGKG RQMPVHYGCK
2bfdA 104 dntdlvfgqa reagvlmyrd yplelfmaqc ygnisdlgkg rqmpvhygck
TARGET sss hhhhh hhhhhhhh h
2bfdA sss hhhhhh hhhhhhhh h
TARGET 199 ERHFVTISSP LATQIPQAVG AAYAAKRANA NRVVICYFGE GAASEGDAHA
2bfdA 154 erhfvtissp latqipqavg aayaakrana nrvvicyfge gaasegdaha
TARGET hhhhhhh hhhhhhhh ssssssss hhh hhhh
2bfdA hhhhhhh hhhhhhhh ssssssss hhh hhhh
TARGET 249 GFNFAATLEC PIIFFCRNNG YAISTPTSEQ YRGDGIAARG PGYGIMSIRV
2bfdA 204 gfnfaatlec piiffcrnng yaistptseq yrgdgiaarg pgygimsirv
TARGET hhhhhhhh ssssssss hhhh hhh sssss
2bfdA hhhhhhhh ssssssss hhhh hhh sssss
TARGET 299 DGNDVFAVYN ATKEARRRAV AENQPFLIEA MTYRIGHHST SDDSSAYRSV
2bfdA 254 dgndvfavyn atkearrrav aenqpfliea mtyrig---- ----------
TARGET ss hhhhhh hhhhhhhhhh hh sssss ss
2bfdA ss hhhhhh hhhhhhhhhh hh sssss ss
TARGET 349 DEVNYWDKQD HPISRLRHYL LSQGWWDEEQ EKAWRKQSRR KVMEAFEQAE
2bfdA 292 -------std hpisrlrhyl lsqgwwdeeq ekawrkqsrr kvmeafeqae
TARGET hhhhhhhh h hhh hhhhhhhhhh hhhhhhhhhh
2bfdA hhhhhhhh h hhh hhhhhhhhhh hhhhhhhhhh
TARGET 399 RKPKPNPNLL FSDVYQEMPA QLRKQQESLA RHLQTYGEHY PLDHFDK
2bfdA 354 rkpkpnpnll fsdvyqempa qlrkqqesla rhlqtygehy pldhfdk-
TARGET h h hhhhhhhhhh hhhhh
2bfdA h h hhhhhhhhhh hhhhh
Prediction for 2r8o_A
TARGET 152 DL -VFG-QYREA ---GVLMYRD --YPLELFMA QCYGNISDLG
2r8oA 52 pswadr--dr fvlsnghgsm liysllhltg ydlpmeelkn -f-rql----
TARGET s ssssss sssssssss
2r8oA s ssss h hhhhhhhh hhhh
TARGET 187 KGRQMPVHYG CK-ERHFVTI SSPLATQIPQ AVGAAYAAKR AN--------
2r8oA 94 -hsktpghpe vgytagvett tgplgqgian avgmaiaekt laaqfnrpgh
TARGET s sssss hhhhh h hhhh hhhhhhhhhh h
2r8oA hhhh hhhhhhhhhh hhhhh
TARGET 228 --ANRVVICY FGEGAASEGD AHAGFNFAAT LEC-PIIFFC RNNGYAISTP
2r8oA 143 divdhytyaf mgdgcmmegi shevcslagt lklgkliafy ddngisidgh
TARGET ssss s hhhh h hhhhhhhhhh h sssss ss sss ss
2r8oA sssss s hhhh h hhhhhhhhhh h ssssss ss sss ss
TARGET 275 TSEQYRGDGI AARGPGYGIM SIR-VDGNDV FAVYNATKEA RRRAVAENQP
2r8oA 193 vegwft-ddt amrfeaygwh virdidghda asikraveea ra---vtdkp
TARGET s h hhhhhhh s sss sss h hhhhhhhhhh h s
2r8oA s h hhhhhh s ss sss h hhhhhhhhhh hh s
TARGET 324 FLIEAMTYRI GHHSTSDDSS ----AYRSVD EVNYWDKQ - ----------
2r8oA 239 sllmcktiig fgspnkagth dshgaplgda eialtreqlg wkyapfeips
TARGET sssssss hh hhhhhhhh
2r8oA sssssss hh hh hhhhhhhhh h
iTasser
2bfd_A
2bfd_A
This prediction is based on several templates fount by iTasser itself.
2.Evaluation of models
As we want to compare the predicted models to the existing PDB entry we need the PDB file for 1U5B. Here only chain A is important, as the sequence for chain A was used to create the models. Therefore chain B has to be removed from the PDB file. Herefore we used a
program names ExtractChains.pl provided by <ref>http://www.rosettacommons.org/guide/PDB+Manipulation+Scripts</ref>.
Swissmodel
Numeric evaluation
QMEAN4 global scores
QMEANscore4
2bfd_A
2r8o_A
0.67
0.271
QMEAN Z-Score
2bfd_A
2r8o_A
-1.604
-6.943
Score components
2bfd_A
2r8o_A
Local scores
2bfd_A
2r8o_A
Global scores: QMEAN4:
2bfd_A
2r8o_A
Scoring function term
Raw score
Z-score
Raw score
Z-score
C_beta interaction energy
-162.66
0.54
-47.91
-1.49
All-atom pairwise energy
-10811.93
0.35
-2558.65
-1.98
Solvation energy
-27.04
-1.02
10.53
-4.08
Torsion angle energy
-75.78
-1.45
18.95
-4.99
QMEAN4 score
0.670
-1.60
0.271
-6.94
Local Model Quality Estimation
2bfd_A
2r8o_A
Comparison to experimental structure
experimental structure
model with template
C-alpha RMSD
1U5B_A
2BFD_A
1.1 [4]
1U5B_A
2R8O_A
2.9 [5]
iTasser
Numeric evaluation
