Team:TU Darmstadt/modelling/Structure

All these steps are performed to every template used for the modeling approach. For our project we set the maximum amount of templates to 20. Every derived structure is evaluated using an average per-residue quality Z-scores. At last a hybrid model is built containing the best regions of all predictions. This procedure make prediction’s accurate and thus more realistic. For the evaluation we used the Yasara Z-scores.A Z-score describes how many standard deviations the model quality is away from the average high-resolution X-ray structure. Negative values indicate that the homology model looks worse than a high-resolution X-ray structure. The overall Z-scores for all models have been calculated as the weighted averages of the individual Z-scores using the formula Overall = 0.145*Dihedrals + 0.390*Packing1D + 0.465*Packing3D [7].

Parameters
We used the Yasara script hm_build.mcr for the model creation with the following parameters:

Modeling speed (slow = best): Slow

Number of PSI-BLAST iterations in template search (PsiBLASTs): 3

Maximum allowed PSI-BLAST E-value to consider template (EValue Max): 0.5

Maximum number of templates to be used (Templates Total): 20

Maximum number of templates with same sequence (Templates SameSeq): 1

Maximum oligomerization state (OligoState): 4 (tetrameric)

Maximum number of alignment variations per template: (Alignments): 5

Maximum number of conformations tried per loop (LoopSamples): 50

Maximum number of residues added to the termini (TermExtension): 10

First model LssmOrange

Here, the hybrid homology model of our protein, LssmOrange is shown in ribbon representation. Furthermore, we illustrate the average quality z-score as a function of residue number. Nevertheless, it was subjected to a final round of simulated annealing minimization in explicit solvent and obtained the following quality Z-scores:

Check Type	Quality Z-score	Comment
Dihedrals	2.363	Optimal
Packing 1D	-0.864	Good
Packing 3D	-1.138	Satisfactory
Overall	-0.524	Good

LssmOrange - second modelling

Check Type	Quality Z-score	Comment
Dihedrals	2.125	Optimal
Packing 1D	-0.936	Good
Packing 3D	-1.259	Satisfactory
Overall	-0.642	Good

Third model LssmOrange (dimer)

Check Type	Quality Z-score	Comment
Dihedrals	1.237	Optimal
Packing 1D	-2.083	Poor
Packing 3D	-1.651	Satisfactory
Overall	-1.400	Satisfactory

References

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[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