Difference between revisions of "Homology-based structure prediction (PKU)"
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The dataset with sequenceidentity from 40% to 80% sequenceidentity only contain structures in connection with aromatic hydroxylation namely Tryptophan and Tyrosin from [http://www.pdb.org/pdb/explore/explore.do?structureId=3e2t chicken] and [http://www.pdb.org/pdb/explore/explore.do?structureId=1toh rat] though the structure gained from the rat also contains the tetramerisation domain we also find in our [http://www.pdb.org/pdb/explore/explore.do?structureId=2pah reference structure]. But we also found Tryptophan and Tyrosin hydroxylase structures in the pdb derived from human.<br> |
The dataset with sequenceidentity from 40% to 80% sequenceidentity only contain structures in connection with aromatic hydroxylation namely Tryptophan and Tyrosin from [http://www.pdb.org/pdb/explore/explore.do?structureId=3e2t chicken] and [http://www.pdb.org/pdb/explore/explore.do?structureId=1toh rat] though the structure gained from the rat also contains the tetramerisation domain we also find in our [http://www.pdb.org/pdb/explore/explore.do?structureId=2pah reference structure]. But we also found Tryptophan and Tyrosin hydroxylase structures in the pdb derived from human.<br> |
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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. |
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. |
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====HHPred==== |
====HHPred==== |
Revision as of 17:09, 29 May 2012
Contents
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 |
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 |
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 |