Difference between revisions of "Homology based structure predictions BCKDHA"

From Bioinformatikpedia
(1.Calculation of models)
(Template selection)
Line 43: Line 43:
 
|}
 
|}
   
> 60% sequence identity:<br>
+
* > 60% sequence identity: 2bfd_A<br>
  +
* > 40% sequence identity: <br>
2bfd_A<br>
 
> 40% sequence identity: <br>
+
* < 40% sequence identity (ideally go towards 20%) :
< 40% sequence identity (ideally go towards 20%) :<br>
 
 
1qs0_A, 1umd_A, 1w85_A, 2r8o_A, 3m49_A, 2ozl_A, 1gpu_A, 3l84_A, 2o1x_A, 1w85_A
 
1qs0_A, 1umd_A, 1w85_A, 2r8o_A, 3m49_A, 2ozl_A, 1gpu_A, 3l84_A, 2o1x_A, 1w85_A
   
Line 57: Line 56:
 
'''2bfd_A''' <br>
 
'''2bfd_A''' <br>
 
< 40% sequence identity (ideally go towards 20%) :<br>
 
< 40% sequence identity (ideally go towards 20%) :<br>
'''2r8o_A'''
+
'''2r8o_A'''
   
 
=== Modeller ===
 
=== Modeller ===

Revision as of 19:25, 10 June 2011

1.Calculation of models

Template selection

Homology modelling is a technique to determine the secondary structure of a target protein. It is based on an alignment of the target sequence and one or more template sequences with known secondary structures. The target sequence is assigned a secondary structure based on the template structure. The better the alignment, the better the predicted secondary structure for our template. Therefore the template selection is a crucial step in homology modelling.

To find similar structures to BCKDHA we ran HHsearch using the following command:
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 modelling 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 modelling 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 template we use the targets (the percentage values indicate the sequence similarity to the target):

  • 1dtw:A 95%
  • 2bfe:A 94%
  • 2bfb:A 99%
  • 2bfd:A 99%
  • 1gpu:A 22%
  • 2o1x:A 18%
  • 2r8o:A 33%

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

Protocol Swissmodel

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


Prediction for 2bfd

Seq    SSLDDKPQFPGASAEFIDKLEFIQPNVISGIPIYRVMDRQGQIINPSEDPHLPKEKVLKLYKSMTLLNTMDRILYESQRQGRISFYMTNYGEEGTHVGSA 
Pred   ccccccccccccccccccccccccccccccccSSSSSccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHcccccccccccccHHHHHHHH
Conf   9867789999988665555664786666789768888999988884236898999999999999999999999999996798467658877389999999

Seq    AALDNTDLVFGQYREAGVLMYRDYPLELFMAQCYGNISDLGKGRQMPVHYGCKERHFVTISSPLATQIPQAVGAAYAAKRANANRVVICYFGEGAASEGD
Pred   HHcccccSSScccHHHHHHHHccccHHHHHHHHHccccccccccccccccccccccccccccHHHccHcHHHHHHHHHHHcccccSSSSSSccccccccc
Conf   9769989775570357899837998999999983777788989998673426212872246336336308999999999709998899994577444210

Seq    AHAGFNFAATLECPIIFFCRNNGYAISTPTSEQYRGDGIAARGPGYGIMSIRVDGNDVFAVYNATKEARRRAVAENQPFLIEAMTYRIGHHSTSDDSSAY
Pred   HHHHHHHHHHHcccSSSSSScccSSccccHHHHHccccHHHHcHcccccSSSSccccHHHHHHHHHHHHHHHHcccccSSSSSSSSSccccccccccccc
Conf   9999999999679979999559821467788772698789843106988689769479999999999999998189988999998750686788998667

Seq    RSVDEVNYWDKQDHPISRLRHYLLSQGWWDEEQEKAWRKQSRRKVMEAFEQAERKPKPNPNLLFSDVYQEMPAQLRKQQESLARHLQTYGEHYPLDHFDK
Pred   ccHHHHHHHHHcccHHHHHHHHHHHcccccHHHHHHHHHHHHHHHHHHHHHHHHcccccHHHHHHHHHccccHHHHHHHHHHHHHHHHccccccHHHHcc
Conf   8999999998639869999999998799999999999999999999999999858998999999675318998899999999999996733188555249 

Secondary structure elements are shown as H for Alpha helix,S for Beta sheet and c for Coil

Additionally iTasser predicts several different models and presents the top five. To predict these models it uses a lot of templates. ITasser searchs the templates itself and also evaluates which one is the best.

2.Evaluation of models

General

A detailed description of how the created models were evaluated can be found in the Evaluation Protocol. The following section presents only the modelling and evaluation results.

Two interesting score when comparing two structures for their structural similarity are the RMSD and the TM-Score. These are two measures which are usually used to measure the accuracy of modelling a structure when the native structure is known.

The RMSD is the average distance of all residue pairs in two structures. The smaller the RMSD value, the better the predicted structure. A local error (e.g. misorientation of the tail) will result in a high RMSD value, although the global structure is correct.

As the RMSD is sensitive to the local error, the TM-Score was proposed. The TM-Score weights close matches stronger than distant matches and therefore the local error problem is overcome. A TM-Score <0.5 indicates a model with random structural similarity, wherease 0.5 < TM-score < 1.00 means the two compared structures are in about the same fold and therefore the predicted model has a correct topology.

Modeller

Numeric evaluation

template molpdf DOPE score GA341 score
2R8O 11049.43 -7610.51 0.00000
2BFD 2247.36 -41979.05 1.00000
1DTW, 1GPU, 2BFB, 2BFD, 2BFE, 2O1X, 2R8O 13873.63 -43399.59 1.00000


The DOPE (Discrete Optimized Protein Energy) score is calculated to assess homology models. The lower the value of the DOPE score the better the . This can be also seen in our three models. The first one (2r8o) which has the worst sequence identity has a quite high DOPE score. The model where 2bfd was the template has a very low score which is reasonable since 2bfd had a very high sequence identity. It is interesting that the model which is build with 7 templates has a higher score than the one which is only build with 1bfd. This can be explained by the influence of the templates which have a low sequence identity with 1u5b.

GA341 is calculated to decide wether the result is a good model or not. A model which is quite good has a score near one. When a model has a score lower than 0.6 it is a bad model. This is also reflected by our results. The model with 2r8o as template is not a good model since the sewuence identity was low and also the DOPE score is quite high so it has a GA341 score of 0. This shows that it is a really bad model. The other two models have a GA341 score of one which shows that they are good models.

Comparison to experimental structure

experimental structure model with template C-alpha RMSD
1U5B_A 2R8O_A no value
1U5B_A 2BFD_A 1.1
1U5B_A 1DTW_A, 2BFE_A, 2BFB_A, 2BFD_A, 1GPU_A, 2O1X_A, 2R8O_A 1.4


C-alpha RMSD is a measure of the average deviation in distance between aligned alpha-carbons. The higher this distance value the worse is the model. The first model with 2r8o as template has no C-alpha RMSD since the programm we used could find enough significant similarities because the structures are to dissimilar. The model build with 2bfd has a C-alpha RMSD score of 1.1. This is a very good score. It is interesting that again the model out of the 7 proteins have no better score (1.4). This shows that the model with 2bfd is the best one.

The model which was build with 2r8o was so bad that it was not possible for DaliLite to predict a C-alpha RMSD. So we had to improve it. For this improvement we load the alignment of 1u5b and 2r8o in Jalview <ref>http://www.jalview.org/download.html</ref> to compare the two sequences. To find more equal residues in both sequences we deleted some gaps and checked the Consensus-line to find the amino acids which are in both sequences. With this handmade alignment we repeated the MODELLER-run. To evaluate the resulting model we calculated the C-alpha RMSD and the TMscore.


template C-alpha score TMscore
2r8o 3.1


As we can see the improvement of the alignment was successful since the model has a much better C-alpha score.

Swissmodel

Numeric evaluation

QMEAN4 global scores

QMEANscore4

2bfd_A 2r8o_A
0.67 0.203


QMEANscore4 is calculated to compare whole models. The score ranges between 0 and 1. The higher the value the better is the quality of the model. By comparing the scores of the model with 2bfd as target and 2r8o as target it iat obvious that the first one os the better one since it has a much higher QMEANscore4.


QMEAN Z-Score

2bfd_A 2r8o_A
-1.604 -9.522
Z-Score plot1 2bfd_A
Z-Score plot1 2r8o_A
Z-Score plot2 2bfd_A
Z-Score plot2 2r8o_A


The QMEAN Z-Score represents the absolute quality of a model. Models with a low quality have a strongly negative QMEAN Z-scores. The 2bfd-model has a less negative score than the 2r8o-model which schos again that this model has a better quality.



Score components

2bfd_A 2r8o_A
score components 2bfd_A
score components 2r8o_A


Local scores

2bfd_A 2r8o_A
Coloring by residue error 2bfd_A
Coloring by residue error 2r8o_A
Residue error plot 2bfd_A
Residue error plot 2r8o_A


With the coloring by residue error the inaccuracy of each residue is esitmated . The results are visualised using a color gradient where blue means that assured region and red means that this region is unreliable. In the model of 2bfd there are many blue alpha helices which means that they are right and only a few red coils. Since blue is the dominant color this shows that the model is mainly right. In contrast the other model has a lot of red and orange alpha helices and coils and nearly no blue region. This reflects the bad quality of this model.

The residue error plot shows the predicted error (y-axis) per residue (x-axis). The highest error score of the 2bfd-model is 12 and the average is about 3 whereas the highest peak score of the 2r8o-model is 15 and the average is about 5. Again it can be seen that the 2bfd-model is the better one.


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 74.97 -4.18
All-atom pairwise energy -10811.93 0.35 2113.21 -5.03
Solvation energy -27.04 -1.02 26.87 -5.92
Torsion angle energy -75.78 -1.45 36.84 -6.47
QMEAN4 score 0.670 -1.60 0.203 -9.52


Local Model Quality Estimation

2bfd_A 2r8o_A
Local Model Quality Estimation 2bfd_A
Local Model Quality Estimation 2r8o_A


For the local model quality estimation we chose the ANOLEA potential. This program performs energy calculations on a protein chain. On the y-axis the energyof each amino acid is represented. Negative energy values (in green) represent favourable energy environment whereas positive values (in red) unfavourable energy environment for a given amino acid. The result of the comparison of this estimation between the 2bfd-model and the 2r8o-model is quite clear since nearly the whole left plot is green and nearly the whole right plot is red. These two plots show that the 2bfd-model is much better than the other one.

Comparison to experimental structure

experimental structure model with template C-alpha RMSD TMscore
1U5B_A 2BFD_A 1.1
1U5B_A 2R8O_A 3.1 0.1639


C-alpha RMSD is a measure of the average deviation in distance between aligned alpha-carbons. The higher this distance value the worse is the model. The 2bfd-model has a score of 1.1 and the 2r8o-model has a score of 3.1. This comparison shows clearly that the first model is mcuh better than the second one.

iTasser

Numeric evaluation

C-score

2bfd
model1 model2 model3 model4 model5
1.999 -3.781 -4.970 -4.970 -3.781

The C-score is a measure for the quality of predicted models by I-TASSER. C-score ranges between [-5,2], where a C-score of higher value signifies a model with a high confidence.

Comparison to experimental structure

2bfd 2r8o
No TMscore C-alpha RMSD TMscore C-alpha RMSD
1 0.9709 0.49 0.5190 3.4
2 0.8609 1.44 0.4979 3.2
3 0.8597 1.43 0.4871 3.0
4 0.8549 1.71 0.5354 4.8
5 0.8251 1.73 0.5107 6.0


All of these models are very good which is shown by the table since they have all a high TMscore and a low C-alpha RMSD score. But this is clear because they are the top 5 hits of iTasser. Perhaps the first model is a bit better than the other 4. This can be expected since the Scores are a bit better than of the other 4 models.

Comparison of the methods

modeller

2BFD_A 2R8O_A Multi
C-alpha RMSD TMscore C-alpha RMSD TMscore C-alpha RMSD TMscore
1.1 0.3526 3.1 0.1749 1.4 0.3596

Swissmodel

2BFD_A 2R8O_A
C-alpha RMSD TMscore C-alpha RMSD TMscore
1.1 3.1 0.1639

iTasser

2bfd 2r8o
model1 model2 model3 model4 model5 model1 model2 model3 model4 model5
RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore RMSD TMscore
0.49 0.9709 1.44 0.8609 1.43 0.8597 1.71 0.8549 1.73 0.8251 3.4 0.5190 3.2 0.4979 3.0 0.4871 4.8 0.5354 6.0 0.5107

References

<references />


back to Maple syrup urine disease main page

back to Secondary_Structure_Prediction_BCKDHA