A topological algorithm for identification of structural domains of proteins

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dc.contributor.author Frank Emmert-Streib en_US
dc.contributor.author Arcady Mushegian en_US
dc.date.accessioned 2009-05-05T16:13:10Z
dc.date.available 2007 - en_US
dc.date.available 2009-05-05T16:13:10Z
dc.date.issued 2006-02-17 en_US
dc.identifier.citation Frank Emmert-Streib;Arcady Mushegian: A topological algorithm for identification of structural domains of proteins. BMC Bioinformatics 2007, 8(1):237. en_US
dc.identifier.uri http://www.biomedcentral.com/1471-2105/8/237 en_US
dc.identifier.uri http://hdl.handle.net/2271/586
dc.description.abstract BACKGROUND:Identification of the structural domains of proteins is important for our understanding of the organizational principles and mechanisms of protein folding, and for insights into protein function and evolution. Algorithmic methods of dissecting protein of known structure into domains developed so far are based on an examination of multiple geometrical, physical and topological features. Successful as many of these approaches are, they employ a lot of heuristics, and it is not clear whether they illuminate any deep underlying principles of protein domain organization. Other well-performing domain dissection methods rely on comparative sequence analysis. These methods are applicable to sequences with known and unknown structure alike, and their success highlights a fundamental principle of protein modularity, but this does not directly improve our understanding of protein spatial structure.RESULTS:We present a novel graph-theoretical algorithm for the identification of domains in proteins with known three-dimensional structure. We represent the protein structure as an undirected, unweighted and unlabeled graph whose nodes correspond to the secondary structure elements and edges represent physical proximity of at least one pair of alpha carbon atoms from two elements. Domains are identified as constrained partitions of the graph, corresponding to sets of vertices obtained by the maximization of the cycle distributions found in the graph. When a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. The decision to accept or reject a tentative cut position is based on a specific classifier. The algorithm is applied iteratively to each of the resulting subgraphs and terminates automatically if partitions are no longer accepted. The distribution of cycles is the only type of information on which the decision about protein dissection is based. Despite the barebone simplicity of the approach, our algorithm approaches the best heuristic algorithms in accuracy.CONCLUSION:Our graph-theoretical algorithm uses only topological information present in the protein structure itself to find the domains and does not rely on any geometrical or physical information about protein molecule. Perhaps unexpectedly, these drastic constraints on resources, which result in a seemingly approximate description of protein structures and leave only a handful of parameters available for analysis, do not lead to any significant deterioration of algorithm accuracy. It appears that protein structures can be rigorously treated as topological rather than geometrical objects and that the majority of information about protein domains can be inferred from the coarse-grained measure of pairwise proximity between elements of secondary structure elements. en_US
dc.format.extent 926558 bytes
dc.format.extent 2910 bytes
dc.format.extent 12055 bytes
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dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.format.mimetype application/octet-stream
dc.format.mimetype application/octet-stream
dc.format.mimetype application/octet-stream
dc.language en en_US
dc.language.iso en_US
dc.publisher BioMedCentral en_US
dc.relation.ispartof 1471-2105 en_US
dc.relation.hasversion http://www.biomedcentral.com/content/pdf/1471-2105-8-237.pdf en_US
dc.rights This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en_US
dc.rights.uri http://creativecommons.org/licenses/by/2.0 en_US
dc.subject.mesh Algorithms en_US
dc.subject.mesh Base Sequence en_US
dc.subject.mesh Binding Sites en_US
dc.subject.mesh Chromosome Mapping/ methods en_US
dc.subject.mesh Computer Simulation en_US
dc.subject.mesh DNA-Binding Proteins/ genetics en_US
dc.subject.mesh Internet en_US
dc.subject.mesh Models, Genetic en_US
dc.subject.mesh Molecular Sequence Data en_US
dc.subject.mesh Online Systems en_US
dc.subject.mesh Protein Binding en_US
dc.subject.mesh Sequence Alignment/ methods en_US
dc.subject.mesh Sequence Analysis, DNA/ methods en_US
dc.subject.mesh Sequence Homology, Nucleic Acid en_US
dc.subject.mesh Software en_US
dc.subject.mesh Transcription Factors/ genetics en_US
dc.title A topological algorithm for identification of structural domains of proteins en_US
dc.type article en_US
dc.date.captured 2009-04-27 en_US
dc.identifier.doi doi:10.1186/1471-2105-8-237 en_US
dc.identifier.pmid 16503993 en_US

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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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