Difference between revisions of "Homology-based structure prediction (PKU)"

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Revision as of 18:26, 29 May 2012

Short Task Description

After the sequence based predictions of function and secondary structure for our protein we will determine the 3D structure of the wild type protein and observe the influence one or several SNPs have on this structure. Of the variety of methods to be used for tertiary structure prediction, we choose homology modeling as a first approach to our goal. Read the complete task description here. The protocol of commands and scripts can be found in our journal

Model Construction

Here we will show the steps we took building the models we then use and evaluate. In order to start the sheer model-building we first have to construct some datasets, which will be the founding of our models.

Datasets

These datasets were derived from serveral sources. They all consist of PDB-entries, but we ensured to no include the already known structure of our protein, so we have a better insight in the topic of homology modeling with a completely unknown sequence.

PDBe

<figtable id="tab:datasetpdbe"> Dataset PDBe

pdb ID E-value Identity in %
> 80% sequence identity
2phm 4.1e-148 95.5
40% - 80% sequence identity
2xsn 6e-100 61.1
1toh 1e-99 60.8
3e2t 8.5e-99 64.4
1mlw 1.1e-95 66.1
3hf8 1.5e-92 66.4
< 30% sequence identity
3l0i 6.7 25
3uan 18 24.8
1vkj 20 24.8
3hv0 71 21.7
</figtable>

For this set of datasets we used the webservice of sequence similarity search provieded by the pdb called PDBeXplore, which can be accessed here. In the used dataset (see <xr id="tab:datasetpdbe" /> we restricted the received data from pdb, such as we didnt use the structure of both the monomer and the dimer etc. We also did not use the structure with different ligands in order to keep the variability high.
In the dataset of sequences above 80% we only found one significant hit, which is the structure for Phenylalanine Hydroxilase dephosphorylated. This is a marginal case for the noninclusion of the protein itself, but we decided, since its from another organism, that we include it.
The dataset with sequenceidentity from 40% to 80% sequenceidentity only contain structures in connection with aromatic hydroxylation namely Tryptophan and Tyrosin from chicken and rat though the structure gained from the rat also contains the tetramerisation domain we also find in our reference structure. But we also found Tryptophan and Tyrosin hydroxylase structures in the pdb derived from human.
As for the lower than 30% dataset, we can not really expect to find usefull output here, because the best E-value we could find is 6.7.


HHPred

<figtable id="tab:datasetHHPred"> Dataset HHPred

pdb ID E-value Identity in %
> 80% sequence identity
1phz 1.5e-159 92
1j8u 2.7e-143 100
40% - 80% sequence identity
1toh 4.9e-147 60
1mlw 4.1e-137 65
< 30% sequence identity
3luy 1.3e-17 21
3mwb 7.1e-15 20
2ko1 0.38 11
1zpv 0.26 12
</figtable>

The dataset with the highest sequencesimilarity in <xr id="tab:datasetHHPred"> contains two structures with a very high similarity, with is due to the fact, that the structure is that of the original protein in different states. One is the protein in complex with Tetrahydrobiopterin (BH4), which is a co-factor for the PheOH-activity. The other is the phosphorylated proteinstructure.
In the second dataset (40%-80%) we find two of the structures which were alread explained above


Coma

<figtable id="tab:datasetComa"> Dataset Coma

pdb ID E-value Identity in %
> 80% sequence identity
1phz 1.5e-159 92
1j8u 2.7e-143 100
40% - 80% sequence identity
1toh 4.9e-147 60
1mlw 4.1e-137 65
< 30% sequence identity
3luy 1.3e-17 21
3mwb 7.1e-15 20
2ko1 0.38 11
1zpv 0.26 12
</figtable>

Explanations to dataset pending


Comparison of datasets

pending

Modelevaluation