The Experts below are selected from a list of 31575 Experts worldwide ranked by ideXlab platform
Arne Elofsson - One of the best experts on this subject based on the ideXlab platform.
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The TOPCONS web server for consensus prediction of membrane Protein Topology and signal peptides
Nucleic acids research, 2015Co-Authors: Konstantinos D. Tsirigos, Lukas Kall, Christoph Peters, Nanjiang Shu, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a widely used web server for consensus prediction of membrane Protein Topology. We hereby present a major update to the server, with some substantial improvements, including the following: (i) TOPCONS can now efficiently separate signal peptides from transmembrane regions. (ii) The server can now differentiate more successfully between globular and membrane Proteins. (iii) The server now is even slightly faster, although a much larger database is used to generate the multiple sequence alignments. For most Proteins, the final prediction is produced in a matter of seconds. (iv) The user-friendly interface is retained, with the additional feature of submitting batch files and accessing the server programmatically using standard interfaces, making it thus ideal for proteome-wide analyses. Indicatively, the user can now scan the entire human proteome in a few days. (v) For Proteins with homology to a known 3D structure, the homology-inferred Topology is also displayed. (vi) Finally, the combination of methods currently implemented achieves an overall increase in performance by 4% as compared to the currently available best-scoring methods and TOPCONS is the only method that can identify signal peptides and still maintain a state-of-the-art performance in Topology predictions.
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Rapid membrane Protein Topology prediction
Bioinformatics (Oxford England), 2011Co-Authors: Aron Hennerdal, Arne ElofssonAbstract:Summary: State-of-the-art methods for Topology of α-helical membrane Proteins are based on the use of time-consuming multiple sequence alignments obtained from PSI-BLAST or other sources. Here, we examine if it is possible to use the consensus of Topology prediction methods that are based on single sequences to obtain a similar accuracy as the more accurate multiple sequence-based methods. Here, we show that TOPCONS-single performs better than any of the other Topology prediction methods tested here, but ~6% worse than the best method that is utilizing multiple sequence alignments. Availability and Implementation: TOPCONS-single is available as a web server from http://single.topcons.net/ and is also included for local installation from the web site. In addition, consensus-based Topology predictions for the entire international Protein index (IPI) is available from the web server and will be updated at regular intervals. Contact: [email protected] Supplementary information:Supplementary data are avaliable at Bioinformatics online.
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TOPCONS: consensus prediction of membrane Protein Topology
Nucleic Acids Research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by ~10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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TOPCONS: consensus prediction of membrane Protein Topology.
Nucleic acids research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by approximately 10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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SPOCTOPUS: A combined predictor of signal peptides and membrane Protein Topology
Bioinformatics (Oxford England), 2008Co-Authors: Håkan Viklund, Andreas Bernsel, Marcin J. Skwark, Arne ElofssonAbstract:Summary: SPOCTOPUS is a method for combined prediction of signal peptides and membrane Protein Topology, suitable for genome-scale studies. Its objective is to minimize false predictions of transmembrane regions as signal peptides and vice versa. We provide a description of the SPOCTOPUS algorithm together with a performance evaluation where SPOCTOPUS compares favorably with state-of-the-art methods for signal peptide and Topology predictions. Availability: SPOCTOPUS is available as a web server and both the source code and benchmark data are available for download at http://octopus.cbr.su.se/ Contact: arne@bioinfo.se Supplementary information: Supplementary data are available at Bioinformatics online.
Gunnar Von Heijne - One of the best experts on this subject based on the ideXlab platform.
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control of membrane Protein Topology by a single c terminal residue
Science, 2010Co-Authors: Susanna Seppala, J. S. Slusky, Pilar Llorisgarcera, Mikaela Rapp, Gunnar Von HeijneAbstract:The mechanism by which multispanning helix-bundle membrane Proteins are inserted into their target membrane remains unclear. In both prokaryotic and eukaryotic cells, membrane Proteins are inserted cotranslationally into the lipid bilayer. Positively charged residues flanking the transmembrane helices are important topological determinants, but it is not known whether they act strictly locally, affecting only the nearest transmembrane helices, or can act globally, affecting the Topology of the entire Protein. Here we found that the Topology of an Escherichia coli inner membrane Protein with four or five transmembrane helices could be controlled by a single positively charged residue placed in different locations throughout the Protein, including the very C terminus. This observation points to an unanticipated plasticity in membrane Protein insertion mechanisms.
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Prediction of membrane-Protein Topology from first principles
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Andreas Bernsel, Gunnar Von Heijne, Håkan Viklund, Jenny Falk, Erik Lindahl, Arne ElofssonAbstract:The current best membrane-Protein Topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane Proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among Protein, lipids and water, it should be possible to predict Topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple Topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based Topology predictors. This result suggests that prediction of membrane-Protein Topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.
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Membrane-Protein Topology
Nature Reviews Molecular Cell Biology, 2006Co-Authors: Gunnar Von HeijneAbstract:In the world of membrane Proteins, Topology defines an important halfway house between the amino-acid sequence and the fully folded three-dimensional structure. Although the concept of membrane-Protein Topology dates back at least 30 years, recent advances in the field of translocon-mediated membrane-Protein assembly, proteome-wide studies of membrane-Protein Topology and an exponentially growing number of high-resolution membrane-Protein structures have given us a deeper understanding of how Topology is determined and of how it evolves.
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Improved membrane Protein Topology prediction by domain assignments.
Protein science : a publication of the Protein Society, 2005Co-Authors: Andreas Bernsel, Gunnar Von HeijneAbstract:Topology predictions for integral membrane Proteins can be substantially improved if parts of the Protein can be constrained to a given in/out location relative to the membrane using experimental data or other information. Here, we have identified a set of 367 domains in the SMART database that, when found in soluble Proteins, have compartment-specific localization of a kind relevant for membrane Protein Topology prediction. Using these domains as prediction constraints, we are able to provide high-quality Topology models for 11% of the membrane Proteins extracted from 38 eukaryotic genomes. Two-thirds of these Proteins are single spanning, a group of Proteins for which current Topology prediction methods perform particularly poorly.
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Confronting fusion Protein-based membrane Protein Topology mapping with reality: the Escherichia coli ClC chloride channel
2005Co-Authors: Marika Cassel, Gunnar Von HeijneAbstract:The major aim of the studies that this thesis is based on has been to better define the topological determinants of the formation of so-called helical hairpins during membrane Protein assembly in the ER membrane.The helical hairpin is a basic folding unit in membrane Proteins. It is composed of two closely spaced transmembrane helices with a short connecting loop and it is believed to be inserted into the membrane as one compact unit. It is becoming increasingly clear that the helical hairpin is a very common structural element in membrane Proteins and a detailed understanding of its properties is of central importance.We demonstrate that the efficiency of formation of helical hairpins depends both on the overall length of the hydrophobic segment, on the amino acids flanking the transmembrane segment, and on the identity of the central, potentially turn-forming residues. We also show that interhelical hydrogen bonds between pairs of Asn or Asp residues can induce helical hairpin formation.A detailed Topology mapping is also reported for the Escherichia coli inner membrane chloride channel YadQ, a Protein for which the X-ray structure is known. Our results provide a critical test of the reporter fusion approach and offer new insights into the YadQ folding pathway.In summary, the results present in this thesis have increased our understanding of the determinants of membrane Protein Topology and structure. Furthermore, the information obtained can be used to improve current models for predictions of membrane Protein Topology.
Janet M. Thornton - One of the best experts on this subject based on the ideXlab platform.
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Protein structural Topology automated analysis and diagrammatic representation
Protein Science, 2008Co-Authors: David R Westhead, Janet M. Thornton, Timothy W F Slidel, Tomas P J FloresAbstract:The Topology of a Protein structure is a highly simplified description of its fold including only the sequence of secondary structure elements, and their relative spatial positions and approximate orientations. This information can be embodied in a two-dimensional diagram of Protein Topology, called a TOPS cartoon. These cartoons are useful for the understanding of particular folds and making comparisons between folds. Here we describe a new algorithm for the production of TOPS cartoons, which is more robust than those previously available, and has a much higher success rate. This algorithm has been used to produce a database of Protein Topology cartoons that covers most of the data bank of known Protein structures.
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motif based searching in tops Protein Topology databases
Bioinformatics, 1999Co-Authors: David Gilbert, David R Westhead, Nozomi Nagano, Janet M. ThorntonAbstract:MOTIVATION TOPS cartoons are a schematic ion of Protein three-dimensional structures in two dimensions, and are used for understanding and manual comparison of Protein folds. Recently, an algorithm that produces the cartoons automatically from Protein structures has been devised and cartoons have been generated to represent all the structures in the structural databank. There is now a need to be able to define target topological patterns and to search the database for matching domains. RESULTS We have devised a formal language for describing TOPS diagrams and patterns, and have designed an efficient algorithm to match a pattern to a set of diagrams. A pattern-matching system has been implemented, and tested on a database derived from all the current entries in the Protein Data Bank (15,000 domains). Users can search on patterns selected from a library of motifs or, alternatively, they can define their own search patterns. AVAILABILITY The system is accessible over the Web at http://tops.ebi.ac.uk/tops
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An algorithm for automatically generating Protein Topology cartoons.
Protein engineering, 1994Co-Authors: T.p. Flores, D. S. Moss, Janet M. ThorntonAbstract:An algorithm is described for automatically generating Protein Topology cartoons. This algorithm optimally places circles and triangles depicting alpha-helices and beta-strands respectively giving a pictorial topological summary of any Protein structure. beta-Sheets, sandwiches and barrels are automatically identified and represented using special templates. The output from this algorithm may be controlled by adjustment of variable weights during the optimization step giving a preferred result. The rules for generating Protein toplogy cartoons, including consideration of the handedness of local structure motifs, are discussed. The design of this algorithm is completely general and is easily adapted to include further rules that dictate the generation of the cartoons.
Andreas Bernsel - One of the best experts on this subject based on the ideXlab platform.
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TOPCONS: consensus prediction of membrane Protein Topology.
Nucleic acids research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by approximately 10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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TOPCONS: consensus prediction of membrane Protein Topology
Nucleic Acids Research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by ~10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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SPOCTOPUS: A combined predictor of signal peptides and membrane Protein Topology
Bioinformatics (Oxford England), 2008Co-Authors: Håkan Viklund, Andreas Bernsel, Marcin J. Skwark, Arne ElofssonAbstract:Summary: SPOCTOPUS is a method for combined prediction of signal peptides and membrane Protein Topology, suitable for genome-scale studies. Its objective is to minimize false predictions of transmembrane regions as signal peptides and vice versa. We provide a description of the SPOCTOPUS algorithm together with a performance evaluation where SPOCTOPUS compares favorably with state-of-the-art methods for signal peptide and Topology predictions. Availability: SPOCTOPUS is available as a web server and both the source code and benchmark data are available for download at http://octopus.cbr.su.se/ Contact: arne@bioinfo.se Supplementary information: Supplementary data are available at Bioinformatics online.
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Prediction of membrane-Protein Topology from first principles
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Andreas Bernsel, Gunnar Von Heijne, Håkan Viklund, Jenny Falk, Erik Lindahl, Arne ElofssonAbstract:The current best membrane-Protein Topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane Proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among Protein, lipids and water, it should be possible to predict Topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple Topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based Topology predictors. This result suggests that prediction of membrane-Protein Topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.
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Improved membrane Protein Topology prediction by domain assignments.
Protein science : a publication of the Protein Society, 2005Co-Authors: Andreas Bernsel, Gunnar Von HeijneAbstract:Topology predictions for integral membrane Proteins can be substantially improved if parts of the Protein can be constrained to a given in/out location relative to the membrane using experimental data or other information. Here, we have identified a set of 367 domains in the SMART database that, when found in soluble Proteins, have compartment-specific localization of a kind relevant for membrane Protein Topology prediction. Using these domains as prediction constraints, we are able to provide high-quality Topology models for 11% of the membrane Proteins extracted from 38 eukaryotic genomes. Two-thirds of these Proteins are single spanning, a group of Proteins for which current Topology prediction methods perform particularly poorly.
Håkan Viklund - One of the best experts on this subject based on the ideXlab platform.
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TOPCONS: consensus prediction of membrane Protein Topology.
Nucleic acids research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by approximately 10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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TOPCONS: consensus prediction of membrane Protein Topology
Nucleic Acids Research, 2009Co-Authors: Andreas Bernsel, Håkan Viklund, Aron Hennerdal, Arne ElofssonAbstract:TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane Protein Topology. The underlying algorithm combines an arbitrary number of Topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the Protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available Topology prediction methods, and for sequences with high reliability scores, performance is increased by ~10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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SPOCTOPUS: A combined predictor of signal peptides and membrane Protein Topology
Bioinformatics (Oxford England), 2008Co-Authors: Håkan Viklund, Andreas Bernsel, Marcin J. Skwark, Arne ElofssonAbstract:Summary: SPOCTOPUS is a method for combined prediction of signal peptides and membrane Protein Topology, suitable for genome-scale studies. Its objective is to minimize false predictions of transmembrane regions as signal peptides and vice versa. We provide a description of the SPOCTOPUS algorithm together with a performance evaluation where SPOCTOPUS compares favorably with state-of-the-art methods for signal peptide and Topology predictions. Availability: SPOCTOPUS is available as a web server and both the source code and benchmark data are available for download at http://octopus.cbr.su.se/ Contact: arne@bioinfo.se Supplementary information: Supplementary data are available at Bioinformatics online.
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Prediction of membrane-Protein Topology from first principles
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Andreas Bernsel, Gunnar Von Heijne, Håkan Viklund, Jenny Falk, Erik Lindahl, Arne ElofssonAbstract:The current best membrane-Protein Topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane Proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among Protein, lipids and water, it should be possible to predict Topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple Topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based Topology predictors. This result suggests that prediction of membrane-Protein Topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.
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best α helical transmembrane Protein Topology predictions are achieved using hidden markov models and evolutionary information
Protein Science, 2004Co-Authors: Håkan Viklund, Arne ElofssonAbstract:Methods that predict the Topology of helical membrane Proteins are standard tools when analyzing any proteome. Therefore, it is important to improve the performance of such methods. Here we introduce a novel method, PRODIV-TMHMM, which is a profile-based hidden Markov model (HMM) that also incorporates the best features of earlier HMM methods. In our tests, PRODIV-TMHMM outperforms earlier methods both when evaluated on “low-resolution” Topology data and on high-resolution 3D structures. The results presented here indicate that the Topology could be correctly predicted for approximately two-thirds of all membrane Proteins using PRODIV-TMHMM. The importance of evolutionary information for Topology prediction is emphasized by the fact that compared with using single sequences, the performance of PRODIV-TMHMM (as well as two other methods) is increased by approximately 10 percentage units by the use of homologous sequences. On a more general level, we also show that HMM-based (or similar) methods perform superiorly to methods that focus mainly on identification of the membrane regions.
