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Team:TU Darmstadt/modelling/Structure
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While our proteins are functionally described in literature and during the IGEM competition, only part of the structures are available in the protein data bank. For further work and visualizations, protein structures are indispensable. We used Yasara Structure [1] to calculate 3-dimensional structures of all of our proteins for the IGEM. | While our proteins are functionally described in literature and during the IGEM competition, only part of the structures are available in the protein data bank. For further work and visualizations, protein structures are indispensable. We used Yasara Structure [1] to calculate 3-dimensional structures of all of our proteins for the IGEM. | ||
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Revision as of 22:05, 3 October 2013
Homology Modelling
While our proteins are functionally described in literature and during the IGEM competition, only part of the structures are available in the protein data bank. For further work and visualizations, protein structures are indispensable. We used Yasara Structure [1] to calculate 3-dimensional structures of all of our proteins for the IGEM.
Workflow
Description how our Yasara script calculates homology model[7]:
- Sequence is PSI-BLASTed against Uniprot [2]
- Calculation of a position-specific scoring matrix (PSSM) from related sequences
- Using the PSSM to search the PDB for potential modeling templates
- The Templates are ranked based on the alignment score and the structural quality[3]
- Deriving additional information’s for template and target (prediction of secondary structure, structure-based alignment correction by using SSALN scoring matrices [4]).
- A graph of the side-chain rotamer network is built, dead-end elimination is used to find an initial rotamer solution in the context of a simple repulsive energy function [5]
- The loop-network is optimized using a high amount of different orientations
- Side-chain rotamers are fine-tuned considering electrostatic and knowledge-based packing interactions as well as solvation effects.
- An unrestrained high-resolution refinement with explicit solvent molecules is run, using the latest knowledge-based force fields[6].
References
[1] E. Krieger, G. Koraimann, and G. Vriend, “Increasing the precision of comparative models with YASARA NOVA--a self-parameterizing force field.,” Proteins, vol. 47, no. 3, pp. 393–402, 2002.
[2] S. F. Altschul, T. L. Madden, A. A. Schäffer, J. Zhang, Z. Zhang, W. Miller, and D. J. Lipman, “Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.,” Nucleic Acids Res, vol. 25, no. 17, pp. 3389–3402, Sep. 1997.
[3] R. W. Hooft, G. Vriend, C. Sander, and E. E. Abola, “Errors in protein structures.,” Nature, vol. 381, no. 6580. Nature Publishing Group, p. 272, 1996.
[4] D. T. Jones, “Protein secondary structure prediction based on position-specific scoring matrices,” Journal of Molecular Biology, vol. 292, no. 2, pp. 195–202, 1999.
[5] A. A. Canutescu, A. A. Shelenkov, and R. L. Dunbrack, “A graph-theory algorithm for rapid protein side-chain prediction.,” Protein Science, vol. 12, no. 9, pp. 2001–2014, 2003.
[6] E. Krieger, K. Joo, J. Lee, J. Lee, S. Raman, J. Thompson, M. Tyka, D. Baker, and K. Karplus, “Improving physical realism, stereochemistry, and side-chain accuracy in homology modeling: Four approaches that performed well in CASP8.,” Proteins, vol. 77 Suppl 9, no. June, pp. 114–122, 2009.
[7] http://www.yasara.org/homologymodeling.htm
