Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9778
Title: Structural alphabets derived from attractors in conformational space
Authors: Pandini, A
Fornili, A
Kleinjung, J
Keywords: Protein structures;'States';Frequently occurring conformations
Issue Date: 2010
Publisher: BMC Bioinformatics
Citation: BMC Bioinformatics, 11, 2010
Abstract: Background: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis.Results: A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness.Conclusions: The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics. © 2010 Pandini et al; licensee BioMed Central Ltd.
URI: http://www.biomedcentral.com/1471-2105/11/97
http://bura.brunel.ac.uk/handle/2438/9778
DOI: http://dx.doi.org/10.1186/1471-2105-11-97
ISSN: 1471-2105
Appears in Collections:Biological Sciences
Dept of Life Sciences Research Papers

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