Team:TU-Munich/Modeling/Protein Predictions
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The prediction of the signal peptides was carried out for different receptors and will be illustrated for the three mentioned examples for which a signal peptide could be identified (see fig. 3). <br> | The prediction of the signal peptides was carried out for different receptors and will be illustrated for the three mentioned examples for which a signal peptide could be identified (see fig. 3). <br> | ||
- | The figure shows the N-terminal sequence of the receptors together with three scores: (1)the C-score (raw cleavage site score) in red, (2) the S-score (signal peptide score) in green and (3) the Y-score (combined cleavage site score) in blue. | + | The figure shows the N-terminal sequence of the receptors together with three scores: (1) the C-score (raw cleavage site score) in red, (2) the S-score (signal peptide score) in green and (3) the Y-score (combined cleavage site score) in blue. |
Revision as of 22:05, 2 July 2013
Prediction of Protein Structures
Table 1:
Predicted Structures | |||
Search for Homologous Structures using HHprd
Prediction of Possible Structure using iTasser
Analysis of Receptor Sequences
For several purposes in our project we needed a synthetic receptor that enables us to express protein-domains at the cellular or extracellular side of the cell membrane. As a template we investigated several different plant-receptors form the well understood dicotyledon Arabidopsis thaliana and the moss we are currently using as our chassis Physcomitrella patens. The A. taliana-receptors have the advantage that their transgenic expression has successfully been demonstrated (Ref.) whereas the P. patens-receptors bear less risk that they do not function in the evolutionary distant moss (Ref).
As there were many different availible receptors that we could use as a template for our synthetic receptor we applied bioinformatical methods to evaluate the suitability of thes receptors. From this work the three examples ERF, FLS2 and SERK are shown (see Table 2).
Table 2:
Examined Receptors | |||
Receptor | Organism | Length (aa) | Sequence reference |
ERF | A. thaliana | 1031 | [http://www.ncbi.nlm.nih.gov/protein/NP_197548.1 NP_197548.1] |
FLS2 | A. thaliana | 1173 | [http://www.ncbi.nlm.nih.gov/protein/NP_199445.1 NP_199445.1] |
SERK | P. patens | 625 | [http://www.ncbi.nlm.nih.gov/protein/XP_001759122.1 XP_001759122.1] |
Prediction of Signal Peptides
Introduction: The first analysis were performed to identify the signal-peptide that is bound by the cellular signal recognition particle and lead to the translocation of the polypeptide into the ER. The signal peptide becomes afterwards cleaved by a signal peptidase at a distict site. The analysis of the signal peptides was carried out using the [http://www.cbs.dtu.dk/services/SignalP SignalP 4.1 Server].
Results:
The prediction of the signal peptides was carried out for different receptors and will be illustrated for the three mentioned examples for which a signal peptide could be identified (see fig. 3).
The figure shows the N-terminal sequence of the receptors together with three scores: (1) the C-score (raw cleavage site score) in red, (2) the S-score (signal peptide score) in green and (3) the Y-score (combined cleavage site score) in blue.
Discussion:
Prediction of Transmembrane Regions
Introduction: [http://www.cbs.dtu.dk/services/TMHMM TMHMM]
Results:
Discussion:
Prediction of Cellular Localization
Introduction: [http://wolfpsort.org Wolfpsort]
Results:
Discussion:
Choice of the SERK Receptor
Analysis of Protein-Ligand Interaction
Structure based prediction using PDBePISA
References:
http://www.ncbi.nlm.nih.gov/pubmed/6327079 Edens et al., 1984
- http://www.ncbi.nlm.nih.gov/pubmed/6327079 Edens et al., 1984 Edens, L., Bom, I., Ledeboer, A. M., Maat, J., Toonen, M. Y., Visser, C., and Verrips, C. T. (1984). Synthesis and processing of the plant protein thaumatin in yeast. Cell, 37(2):629–33.
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