Figure 7.5. 3D-JIGSAW (web server) BSA predicted structure. The method is fragment based, the whole sequence of BSA is necessarry.
On the basis of the frequency of aminoacids in BSA and HSA, it can be seen that they are very similar.
Figure 7.6. EsyPred3D (web server): BSA predicted structure. The method is fragment based, the whole sequence of BSA is necessarry. The applied structure was 1AO6 (HSA). The template-target identity 72,6%.
Figure 7.7. LOMETS (web server): BSA predicted structure. The method is fragment based, the whole sequence of BSA is necessarry. The applied structure was 1n5u (HSA). The template-target identity 72,6%.
Figure 7.8. Swiss-Prot (web server): BSA predicted structure.
Figure 7.9. Gen3D, homology modelling with constraints.
Figure 7.10. CBS (web server): BSA predicted structure.
The real XRD structure of BSA was published: PDB Id.:3V03. The molecule is important in the bionano experiment to hydrophylize (capsulate) hydrophobic drug molecules in drug delivery. A checking homology modelling was applid for HSA from the obtained BSA model. Its goodness (RMSD) can be seen in Table 7.6.
Table 7.5. RMSD values calculated by VMD [9] (the numbers in parenthesis are the number of residues considered int he calculations)
|
HSA
|
HSA
|
CBS
|
ESYPRED
|
GENO
|
LOMETS
|
SWISS
|
HSA
|
|
24,77(480)
|
24,77(480)
|
0,4423(570)
|
5,626(420)
|
24,74(475)
|
5,788(495)
|
3DJIGSAW
|
24,77(480)
|
|
24,45(545)
|
25,18(565)
|
24,93(545)
|
0,753(485)
|
24,69(565)
|
CBS
|
24,77(480)
|
24,45(545)
|
|
4,136(445)
|
4,451(545)
|
24,44(485)
|
0,7926(565)
|
ESYPRED
|
0,4423(570)
|
25,18(565)
|
4,136(445)
|
|
6,037(515)
|
24,68(485)
|
5,989(565)
|
GENO
|
5,626(420)
|
24,93(545)
|
4,451(545)
|
6,037(515)
|
|
24,74(485)
|
4,338(565)
|
LOMETS
|
24,74(475)
|
0,753(485)
|
24,44(485)
|
24,68(485)
|
24,74(485)
|
|
24,60(485)
|
SWISS
|
5,788(495)
|
24,69(565)
|
0,7926(565)
|
5,989(565)
|
4,338(565)
|
24,60(485)
|
|
To refine the structure, it is important to optimize the structure. The pKa of the side chains were calculated. The structures were optimized by TINKER/AMBER99 and AMBER99/GBSA (see Chapter 1). The result compared with the unoptimized structures can be seen in Figure 7.11.
The structure is acceptable after optimization by real empirical folding force field foldX [10], which is an excellent method after homology modelling.
A good choice in homology modelling and analysis of proteins is the CLCBio [11]. The structures after the generation of the structures must be optimized. The strains can be decreased by optimization and after this procedure MD calculations (e.g. gromacs) are necessarry [12,13].
Figure 7.11. Optimized geometries of the BSA structures ontained by homology modelling (TINKER/AMBER99 and TINKER/AMBER99/GBSA)
Figure 7.12. Ramachandran plots of BSA before optimization and after optimization (the optimization of the empty plots were not successful).
For the initial structure of the proteins it is suggested to perform MD calculations of the structures obtained by XRD. In the end of the homology modelling or loop prediction to reduce the strain also MD simulation is suggested. Fort he optimal initial structure of side chains can be obtained by SCWRL4 method [14].
Docking with ligands can help to validate the structure of the proteins obtained by homology modelling. The ligand-protein complex structure have to be known.
5. Summary
The missing 3D structures in proteins can be predicted by homology modeling. The ab initio structure prediction is not really reliable, our knowledge is lacking. Different strategies are supported by the homology modelling methods. There are some methods to check the goodness of the models.
6. References
D Baker, A Sali, Protein Structure Prediction and Structural Genomics , Science 294, 93-96 (2001).
http://ekhidna.biocenter.helsinki.fi/dali_lite/start
http://www.cathdb.info/cgi-bin/SsapServer.pl
http://cl.sdsc.edu/ce/ce_align.html
http://biunit.aist-nara.ac.jp/matras/matras_pair.html
http://amazon-tip64.eidogen-sertanty.com/Login.po
http://wishart.biology.ualberta.ca/SuperPose/
http://www.ncbi.nlm.nih.gov/Structure/VAST/vast.shtml
W. Humphrey, A. Dalke, K. Schulten, VMD - Visual Molecular Dynamics. J. of Mol.
Graph., 14:33-38(1996).
J. W. Schymkowitz, F. Rousseau, I. C. Martins, J. Ferkinghoff-Borg, F. Stricher, L. Serrano L., Prediction of water and metal binding sites and their affinities by using the Fold-X force field.Proc Natl Acad Sci U S A,102(29):10147-52(2005).
http://www.clcbio.com/index.php?id=28
http://www.gromacs.org
http://research.ozreef.org/GROMACS_MD_Flowchart.pdf
http://dunbrack.fccc.edu/scwrl4/SCWRL4.php
7. Further Readings
Bioinformatics, A Practical Guide to the Analysis of Genes and Proteins. 2nd Ed., Ed. A. D. Baxevanis, B.F. F. Quelette,Wiley Interscience John Wiley & Sons, Inc. Publication, 2001.
C. Gibas, P. Jambeck, Developing Bioinformatics Computer Skills, O’Reilly & Associates, Inc. 2001.
Structural Bioinformatics, Ed. by P. E. Bourne, H. Weissig, Wiley-Liss, A John Wiley & Sons Publication, 2003.
8. Questions
What is the ab initio prediction of protein structure?
What is the homology modeling and loop prediction?
What is the procedure of homology modeling?
What methods are used in the model generation in homology modelling?
What methods are necessarry after the prediction of the structure in homology modelling?
What methods are known to support the goodness of homology modelling?
What is threading procedure?
9. Glossary
Ab initio protein structure prediction The known sequence without 3D structure demand to predict the 3D structure for modeling. This method can be only a suggestion on the structure, It can contain failures.
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