Team:TU-Munich/Modeling/Protein Predictions
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==Prediction of Protein Structures and Functions== | ==Prediction of Protein Structures and Functions== | ||
Structural properties of effector proteins are often important for their function, so it is advantageous to know about them. It is for example necessary to know whether termini are accessible for protein fusion or whether the protein is only functional in a multimeric fold. For this reason a structure based search was performed in the [http://www.rcsb.org/pdb/home/home.do protein data bank]. As the number of identified structures is still limited, it is a promising attempt to look for homologous proteins whose crystal structures have been determined. | Structural properties of effector proteins are often important for their function, so it is advantageous to know about them. It is for example necessary to know whether termini are accessible for protein fusion or whether the protein is only functional in a multimeric fold. For this reason a structure based search was performed in the [http://www.rcsb.org/pdb/home/home.do protein data bank]. As the number of identified structures is still limited, it is a promising attempt to look for homologous proteins whose crystal structures have been determined. | ||
+ | |||
+ | ==Analysis of Receptor Sequences – Choosing the right template == | ||
+ | |||
+ | For several purposes of our project, we needed a synthetic receptor enabling us to integrate proteins into the membrane in the desired orientation, i.e. to express protein-domains on the intracellular or extracellular side of the cell membrane. We investigated several different plant-receptors from the well characterized dicotyledon ''Arabidopsis thaliana'' and the moss ''Physcomitrella patens'', our chassis. The receptors from ''Arabidopsis thaliana'' have the advantage that their transgenic expression has successfully been demonstrated [[http://www.pnas.org/content/88/23/10806.full.pdf Quail et al., 1991]] whereas the receptors from ''Physcomitrella patens'' bear less risk that they do not work in the evolutionary far distant moss [[http://www.plant-biotech.net/paper/Reski_1998_BotActa-111_1_scan.pdf Reski, 1998]]<br> | ||
+ | Due to the fact that there were many different available receptors, which we could use as a template for our synthetic receptor, we used bioinformatical methods to evaluate the suitability of these receptors. The following three examples ERF, FLS2 and SERK shown in table 2 resulted from this equation. | ||
+ | |||
+ | {|cellspacing="0" border="1" | ||
+ | |+ Table 2: Examined Receptors | ||
+ | !Receptor | ||
+ | !Organism | ||
+ | !Length (aa) | ||
+ | !Sequence reference | ||
+ | !Literature 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] | ||
+ | |[http://www.freidok.uni-freiburg.de/volltexte/5390/pdf/Lienhart_Dissertation_2008.pdf Lienhart, 2007] | ||
+ | |- | ||
+ | |} | ||
+ | <br> | ||
+ | <br> | ||
+ | ===Prediction of Signal Peptides=== | ||
+ | [[File:TUM13 Modeling_Signal-P.png|thumb|right|350px| Figure 3: Prediction and analysis of signal peptides]] | ||
+ | '''Introduction'''<br> | ||
+ | The first analysis was performed to identify a signal-peptide, which is bound by the cellular signal recognition particle and leads to the translocation of the bound polypeptide into the endoplasmic reticulum. The signal peptide afterwards gets cleaved by a signal peptide peptidase at a distinct site. The analysis of the cut-off signal peptide was carried out by using the [http://www.cbs.dtu.dk/services/SignalP SignalP 4.1 Server]. <br> | ||
+ | <br> | ||
+ | '''Results'''<br> | ||
+ | The prediction of the signal peptide was realized for different receptors and will be illustrated for the three examples mentioned above (see fig. 3). <br> | ||
+ | The figure shows the N-terminal sequence of the receptors, together with three scores: <br> | ||
+ | (1) The C-Score (raw cleavage site score) in red. <br> | ||
+ | (2) The S-Score (signal peptide score) in green. <br> | ||
+ | (3) The Y-Score (combined cleavage site score) in blue.<br> | ||
+ | <br> | ||
+ | The C-Score shows the most probable cleavage site, the signal peptidase is identifying. It was possible to identify the most probable cleavage site for all shown receptors with ambiguous cleavage sites for the SERK-receptor. The amino acid with the highest C-score is, according to the algorithm, predicted to be the first amino acid of the primary structure of the cleaved receptor. <br> | ||
+ | The S-Score was developed to identify amino acid sequences which appear in a polypeptide and others that belong to the matured receptor. The course of this parameter is high for the first 23-28 amino acids of all receptors, identifying these residues as signal peptides. The amino acid residue, which lies at the greatest decrease of the S-Score, is the predicted border between the N-terminal signal peptide and the receptor. <br> | ||
+ | The Y-Score results from the geometrical structure of the protein and the predetermined first Scoring parameters. It illustrates that the two first parameters show a good fit for the identification of the signal peptide in all three illustrated receptors.<br> | ||
+ | <br> | ||
+ | '''Discussion'''<br> | ||
+ | Summarizing these parameters, it can be concluded that all three pictured receptors seem to contain a sequence that works as a signal peptide. For many of the predicted receptors in the genome of ''Physcomitrella patens'' the prediction did not yield a positive result. Referring to the signal peptide, all mentioned receptors would be suitable as a template for our synthetic receptor. The predicted data show that the SERK-Receptor is favorable for our application, because it's signal peptide is statistically seen the most recognized one and bears the smallest risk of failure. | ||
+ | |||
+ | <br> | ||
+ | <br> | ||
+ | |||
+ | ===Prediction of Transmembrane Regions=== | ||
+ | [[File:TUM13 Modeling_TMHMM.png|thumb|right|350px| Figure 4:]] | ||
+ | '''Introduction'''<br> | ||
+ | Beside to the identification of the signal peptide, it was very important to identify transmembrane regions within the receptors, because we wanted to use a type I receptor as a template that contains a N-terminal extracellular domain, a Transmembrane-domain region and a C-terminal intracellular domain (see [https://2013.igem.org/Team:TU-Munich/Project/Localisation Localization page]. To analyze this issue, the prediction tool [http://www.cbs.dtu.dk/services/TMHMM TMHMM] was used for several different receptors. Again the most suitable receptors have been ERK, FLS2 and SERK.<br> | ||
+ | <br> | ||
+ | '''Results'''<br> | ||
+ | The analysis yields a signal peptide and a single transmembrane domain for all the depicted receptors (see fig. 4). The estimated reliability of the prediction of the transmembrane region was equally good for all examined receptors, whereas the signalpeptide was predicted best, for the SERK receptor. <br> | ||
+ | <br> | ||
+ | '''Discussion'''<br> | ||
+ | Focussing the membrane topology point of view, all the investigated receptors would be suitable blue prints for our synthetic receptor. As the SERK-Receptor yields the best prediction, it was elected as the favorable template. Another reason to elect the SERK-Receptor was that it is derived from ''Physcomitrella patens''. The only problem, concerning this prediction, is that the N-terminal position of this receptor is predicted to be orientated extracellularly. The falsification of this prediction was simple, as the SERK receptor contains a C-terminal kinase-domain, which is known to be involved in signal transduction. | ||
+ | <br> | ||
+ | <br> | ||
+ | <br> | ||
+ | |||
+ | ===Choice of the SERK Receptor=== | ||
+ | Finally we decided to use the SERK receptor as a template to generate our synthetic receptor. The final receptor was designed in RFC[25] standard, which allows in frame protein fusions. The final constructs were designed containing the SERK signal peptide ([http://parts.igem.org/Part:BBa_K1159303 BBa_K1159303]), an extracellularely located effector protein, the transmembrane domain of the SERK receptor ([http://parts.igem.org/Part:BBa_K1159305 BBa_K1159305]), a short linker and a GFP, to investigate the cellular localization of our receptor with the aid of fluorescense microscopy. | ||
==Searching for Homologous Structures using HHpred== | ==Searching for Homologous Structures using HHpred== | ||
Line 102: | Line 175: | ||
The homology search showed that some of our effector proteins have very closely related proteins with a known structure. For example there are very similar protein structures available for the SypCatcher, PP1 and GFP each with identities of over 90%. Some other effector proteins such as XylE, Laccase or the DDT Dehydrochlorinase have less homologous proteins, whose structures still give good hints on structural questions. However there are also effectors where only badly matched structures are known, which can only be used as a very rough indication of the fold. The NanoLuc luciferase, which is a highly engineered protein derived from shrimps and was only published this year, is an example of a protein with no known structural homologue.<br> | The homology search showed that some of our effector proteins have very closely related proteins with a known structure. For example there are very similar protein structures available for the SypCatcher, PP1 and GFP each with identities of over 90%. Some other effector proteins such as XylE, Laccase or the DDT Dehydrochlorinase have less homologous proteins, whose structures still give good hints on structural questions. However there are also effectors where only badly matched structures are known, which can only be used as a very rough indication of the fold. The NanoLuc luciferase, which is a highly engineered protein derived from shrimps and was only published this year, is an example of a protein with no known structural homologue.<br> | ||
The structures obtained here were used to design our experiments. A homology modeling for the Laccase was performed to determine whether it contains disulphide bridges. The resulting homologous structures were used as illustrations, as explained in one of our [https://2013.igem.org/Team:TU-Munich/Results/How_To How-Tos] about animated GIFs. | The structures obtained here were used to design our experiments. A homology modeling for the Laccase was performed to determine whether it contains disulphide bridges. The resulting homologous structures were used as illustrations, as explained in one of our [https://2013.igem.org/Team:TU-Munich/Results/How_To How-Tos] about animated GIFs. | ||
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==References:== | ==References:== |
Revision as of 01:15, 5 October 2013
Prediction of Protein Structures and Functions
Structural properties of effector proteins are often important for their function, so it is advantageous to know about them. It is for example necessary to know whether termini are accessible for protein fusion or whether the protein is only functional in a multimeric fold. For this reason a structure based search was performed in the [http://www.rcsb.org/pdb/home/home.do protein data bank]. As the number of identified structures is still limited, it is a promising attempt to look for homologous proteins whose crystal structures have been determined.
Analysis of Receptor Sequences – Choosing the right template
For several purposes of our project, we needed a synthetic receptor enabling us to integrate proteins into the membrane in the desired orientation, i.e. to express protein-domains on the intracellular or extracellular side of the cell membrane. We investigated several different plant-receptors from the well characterized dicotyledon Arabidopsis thaliana and the moss Physcomitrella patens, our chassis. The receptors from Arabidopsis thaliana have the advantage that their transgenic expression has successfully been demonstrated http://www.pnas.org/content/88/23/10806.full.pdf Quail et al., 1991 whereas the receptors from Physcomitrella patens bear less risk that they do not work in the evolutionary far distant moss http://www.plant-biotech.net/paper/Reski_1998_BotActa-111_1_scan.pdf Reski, 1998
Due to the fact that there were many different available receptors, which we could use as a template for our synthetic receptor, we used bioinformatical methods to evaluate the suitability of these receptors. The following three examples ERF, FLS2 and SERK shown in table 2 resulted from this equation.
Receptor | Organism | Length (aa) | Sequence reference | Literature 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] | [http://www.freidok.uni-freiburg.de/volltexte/5390/pdf/Lienhart_Dissertation_2008.pdf Lienhart, 2007] |
Prediction of Signal Peptides
Introduction
The first analysis was performed to identify a signal-peptide, which is bound by the cellular signal recognition particle and leads to the translocation of the bound polypeptide into the endoplasmic reticulum. The signal peptide afterwards gets cleaved by a signal peptide peptidase at a distinct site. The analysis of the cut-off signal peptide was carried out by using the [http://www.cbs.dtu.dk/services/SignalP SignalP 4.1 Server].
Results
The prediction of the signal peptide was realized for different receptors and will be illustrated for the three examples mentioned above (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.
(3) The Y-Score (combined cleavage site score) in blue.
The C-Score shows the most probable cleavage site, the signal peptidase is identifying. It was possible to identify the most probable cleavage site for all shown receptors with ambiguous cleavage sites for the SERK-receptor. The amino acid with the highest C-score is, according to the algorithm, predicted to be the first amino acid of the primary structure of the cleaved receptor.
The S-Score was developed to identify amino acid sequences which appear in a polypeptide and others that belong to the matured receptor. The course of this parameter is high for the first 23-28 amino acids of all receptors, identifying these residues as signal peptides. The amino acid residue, which lies at the greatest decrease of the S-Score, is the predicted border between the N-terminal signal peptide and the receptor.
The Y-Score results from the geometrical structure of the protein and the predetermined first Scoring parameters. It illustrates that the two first parameters show a good fit for the identification of the signal peptide in all three illustrated receptors.
Discussion
Summarizing these parameters, it can be concluded that all three pictured receptors seem to contain a sequence that works as a signal peptide. For many of the predicted receptors in the genome of Physcomitrella patens the prediction did not yield a positive result. Referring to the signal peptide, all mentioned receptors would be suitable as a template for our synthetic receptor. The predicted data show that the SERK-Receptor is favorable for our application, because it's signal peptide is statistically seen the most recognized one and bears the smallest risk of failure.
Prediction of Transmembrane Regions
Introduction
Beside to the identification of the signal peptide, it was very important to identify transmembrane regions within the receptors, because we wanted to use a type I receptor as a template that contains a N-terminal extracellular domain, a Transmembrane-domain region and a C-terminal intracellular domain (see Localization page. To analyze this issue, the prediction tool [http://www.cbs.dtu.dk/services/TMHMM TMHMM] was used for several different receptors. Again the most suitable receptors have been ERK, FLS2 and SERK.
Results
The analysis yields a signal peptide and a single transmembrane domain for all the depicted receptors (see fig. 4). The estimated reliability of the prediction of the transmembrane region was equally good for all examined receptors, whereas the signalpeptide was predicted best, for the SERK receptor.
Discussion
Focussing the membrane topology point of view, all the investigated receptors would be suitable blue prints for our synthetic receptor. As the SERK-Receptor yields the best prediction, it was elected as the favorable template. Another reason to elect the SERK-Receptor was that it is derived from Physcomitrella patens. The only problem, concerning this prediction, is that the N-terminal position of this receptor is predicted to be orientated extracellularly. The falsification of this prediction was simple, as the SERK receptor contains a C-terminal kinase-domain, which is known to be involved in signal transduction.
Choice of the SERK Receptor
Finally we decided to use the SERK receptor as a template to generate our synthetic receptor. The final receptor was designed in RFC[25] standard, which allows in frame protein fusions. The final constructs were designed containing the SERK signal peptide ([http://parts.igem.org/Part:BBa_K1159303 BBa_K1159303]), an extracellularely located effector protein, the transmembrane domain of the SERK receptor ([http://parts.igem.org/Part:BBa_K1159305 BBa_K1159305]), a short linker and a GFP, to investigate the cellular localization of our receptor with the aid of fluorescense microscopy.
Searching for Homologous Structures using HHpred
The search for homologous structures was performed by using the freely accessible web server [http://toolkit.tuebingen.mpg.de/hhpred HHpred] http://www.ncbi.nlm.nih.gov/pubmed/15980461 Söding et al., 2005. The amino acid sequences for the BioBricks were translated into amino acid sequences using the AutoAnnotator and was then inserted into the the search field. The results for all proteins investigated in our project are shown in table 1.
Results
The homology search showed that some of our effector proteins have very closely related proteins with a known structure. For example there are very similar protein structures available for the SypCatcher, PP1 and GFP each with identities of over 90%. Some other effector proteins such as XylE, Laccase or the DDT Dehydrochlorinase have less homologous proteins, whose structures still give good hints on structural questions. However there are also effectors where only badly matched structures are known, which can only be used as a very rough indication of the fold. The NanoLuc luciferase, which is a highly engineered protein derived from shrimps and was only published this year, is an example of a protein with no known structural homologue.
The structures obtained here were used to design our experiments. A homology modeling for the Laccase was performed to determine whether it contains disulphide bridges. The resulting homologous structures were used as illustrations, as explained in one of our How-Tos about animated GIFs.
References:
http://www.ncbi.nlm.nih.gov/pubmed/15980461 Söding et al., 2005 Söding J, Biegert A, Lupas AN. (2005). The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W244-8.
http://www.plant-biotech.net/paper/Reski_1998_BotActa-111_1_scan.pdf Reski, 1998 Reski, R. (1998). Development, Genetics and Molecular Biology of Mosses. Bot. Acta, 111:1-15.
http://www.pnas.org/content/88/23/10806.full.pdf Quail et al., 1991 MARGARET T. Boylan, M.T. and Quail, P.H. (1991). PhytochromeA overexpression inhibits hypocotyl elongation in transgenic Arabidopsis. Proc. Natl. Acad. Sci. 88:10806-10810.
http://www.freidok.uni-freiburg.de/volltexte/5390/pdf/Lienhart_Dissertation_2008.pdf Lienhart, 2007 Lienhart, O. (2007). Untersuchungen zu einem Somatic-Embryogenesis-Receptor-like-Kinase-Homolog in Physcomitrella patens (Hedw.) B.S.G. PhD-thesis at Freiburg University
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