Difference between revisions of "Task 5: Homology Modeling"

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Revision as of 23:54, 26 August 2013

lab journal task 5

1A6Z chain A was used as modeling target for all three methods.

Modeller

We used Modeller to create models based on a single template and multiple templates.


Single template

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<figtable id="Modeller single">

Template Seq. identity std Alignment 2d alignment curated Alignment
DOPE score RMSD GDT score DOPE score RMSD GDT score DOPE score RMSD GDT score
1QVO_A 39% -27772 3.647 0.6241 -27169 4.994 0.5653
1S7X_A 29% -19941 15.806 0.3355 -18667 18.099 0.2509
1CD1_A 21% -19034 18.066 0.3640 -24213 5.640 0.4697
Table 1: Template structures and their sequence identity to the target, as computed by Blast. The DOPE score, RMSD and GDT score are given as a quality measure. The different models were created based on pairwise sequence alignments with dynamic programming (std Alignment), pairwise sequence alignment with additional secondary structure information (2d Alignment) and manually curated alignments (curated Alignment).

</figtable>

<xr id="Modeller single"/> lists the selected templates and the Modeller results for the different template structures and alignment methods. In addition to the standard pairwise sequence alignment based on dynamic programming, we also used Modeller's alignment.alig2dn() method to improve the alignment by including secondary structure information and improved the alignments manually. As Modeller quality score, we chose the DOPE score, which is a statistical potential that was optimized for the assessment of model quality. The DOPE score has an arbitrary scale, but scores for structures of the same protein are comparable and can be used to select the best model from a collection of structures. The lower the score, the better the model. In addition to the DOPE score, we also computed the RMSD and GDT score. The RMSD is a a good measure of the average distance between all pairs of corresponding atoms in two structures. Therefore, the lower the RMSD the better. For the GDT score, the average coverage of the target sequence under four defined distance cutoffs is computed. Normally, 1, 2, 4 and 8 Å are used as distance thresholds. The GDT score ranges between 0 and 1, with random superpositions of unrelated structures having a score of 0.1 to 0.2.

Including the secondary structure information did only improve the model of the most distant homolog 1CD1_A.


<figtable id="pymol str. al.">

a) classical pairwise sequence alignment
b) inclusion of secondary structure information in the alignment
Figure 1: Superposition of the target 1A6Z_A (green), the template 1QVO_A (red) and the model (purple). Two different alignment methods were used to create the input alignment. for Modeller.

</figtable>


<figtable id="pymol str. al.">

a) classical pairwise sequence alignment
b) inclusion of secondary structure information in the alignment
Figure 2: Superposition of the target 1A6Z_A (green), the template 1S7X_A (red) and the model (purple). Two different alignment methods were used to create the input alignment. for Modeller.

</figtable>


<figtable id="pymol str. al.">

a) classical pairwise sequence alignment
b) inclusion of secondary structure information in the alignment
Figure 3: Superposition of the target 1A6Z_A (green), the template 1CD1_A (red) and the model (purple). Two different alignment methods were used to create the input alignment. for Modeller.

</figtable>

Multiple templates

We also user more than one template in a modeling step. Therefore, we created three sets of structures, one with close homologes, one with distant homologes and one combined set.

<figtable id="multiple sets">

close homology distant homology mixed
Template Seq. identity Template Seq. identity Template Seq. identity
1QVO_A 39% 3HUJ_C 23% 1QVO_A 39%
1ZAG_A 36% 1CD1_A 21% 1CD1_A 21%
1RJZ_D 34% 1VZY_A 14%
Table 2: The three different sets used as templates for Modeller: two sets of close and distant homologs and a mixed set.

</figtable>

<xr id="multiple sets"/> specifies the three sets.

<figtable id="multiple sets">

close homology distant homology mixed homology
Template 1QVO_A, 1ZAG_A 1QVO_A, 1ZAG_A, 1RJZ_D 3HUJ_C, 1CD1_A 3HUJ_C, 1CD1_A, 1VZY_A 1QVO_A, 1CD1_A
DOPE score -28073 -27460 -25967 -20588 -25894
RMSD 3.432 2.431 4.130 7.741 3.974
GDT score 0.6553 0.7638 0.5607 0.3814 0.5846
Pymol visualisation
Visualisation of the target (green) and the model created from 1QVO_A and 1ZAG_A (purple).
Visualisation of the target (green) and model created from 1QVO_A, 1ZAG_A and 1RJZ_D (purple).
Visualisation of the target (green) and model model created from 3HUJ_C and 1CD1_A (purple).
Visualisation of the target (green) and model created from 3HUJ_C, 1CD1_A and 1VZY_A (purple).
Visualisation of the target (green) and the model created from 1QVO_A and 1CD1_A (purple).
Table 3: Results of the modeling with multiple templates. We computed models using 2 structures as templates and also using three structures.

</figtable>

Swiss-Model

We used Swiss-Model to create models using 1QVO_A, 1S7X_A and 1CD1_A as template.

<figtable id="swiss-model">

1QVO_A 1S7X_A 1CD1_A
Seq. identity 39% 29% 21%
Z-score -1.977 -2.005 -2.707
RMSD 2.847 2.757 3.604
GDT score 0.6774 0.7086 0.6121
Pymol visualisation
Visualisation of the target (green), the template 1QVO_A and the model (purple).
Visualisation of the target (green), the template 1S7X-A and the model (purple).
Visualisation of the target (green), the template 1CD1_A and the model (purple).
Anolea and Gromos energy
1qvo anolea.png
1s7x anolea.png
1cd1 anolea.png
Table 4: Overview of the Swiss-Model results for the three different templates.

</figtable>

Swiss-Model outputs a raw score and also a Z-score that represents an absolute measure of the model quality. It relates the model's raw score to the scores that high-resolution X-ray structures get and thus gives an estimate of how likely the model has a quality comparable to an experimental structure. A low quality model is indicated by a strong negative Z-score, which means that the raw score is several standard deviations lower as the scores of experimental structures with similar size (see Swiss-Model help).

Swiss-Model also provides plots that help to analyse the local energy of the model. For this, the atomic empirical mean force potential (Anolea) and the Gromos simulation package are used. Both are used calculate the energy of each amino acid in the sequence. The two plots show the protein sequence on the x-axis and the calculated energy of each residue on the y-axis. A low energy corresponds to a favorable energy environment for an amino acid and a positive energy represents an unfavorable energy environment.

I-TASSER

<figtable id="i-tasser">

1QVO_A 1CD1_A
Seq. identity
C-score
RMSD
GDT score
Pymol visualisation
Visualisation of the target (green), the template 1QVO_A and the model (purple).
Visualisation of the target (green), the template 1CD1_A and the model (purple).

</figtable>