Literature DB >> 15215530

Structural alignment of proteins by a novel TOPOFIT method, as a superimposition of common volumes at a topomax point.

Valentin A Ilyin1, Alexej Abyzov, Chesley M Leslin.   

Abstract

Similarity of protein structures has been analyzed using three-dimensional Delaunay triangulation patterns derived from the backbone representation. It has been found that structurally related proteins have a common spatial invariant part, a set of tetrahedrons, mathematically described as a common spatial subgraph volume of the three-dimensional contact graph derived from Delaunay tessellation (DT). Based on this property of protein structures, we present a novel common volume superimposition (TOPOFIT) method to produce structural alignments. Structural alignments usually evaluated by a number of equivalent (aligned) positions (N(e)) with corresponding root mean square deviation (RMSD). The superimposition of the DT patterns allows one to uniquely identify a maximal common number of equivalent residues in the structural alignment. In other words, TOPOFIT identifies a feature point on the RMSD N(e) curve, a topomax point, until which the topologies of two structures correspond to each other, including backbone and interresidue contacts, whereas the growing number of mismatches between the DT patterns occurs at larger RMSD (N(e)) after the topomax point. It has been found that the topomax point is present in all alignments from different protein structural classes; therefore, the TOPOFIT method identifies common, invariant structural parts between proteins. The alignments produced by the TOPOFIT method have a good correlation with alignments produced by other current methods. This novel method opens new opportunities for the comparative analysis of protein structures and for more detailed studies on understanding the molecular principles of tertiary structure organization and functionality. The TOPOFIT method also helps to detect conformational changes, topological differences in variable parts, which are particularly important for studies of variations in active/ binding sites and protein classification.

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Year:  2004        PMID: 15215530      PMCID: PMC2279929          DOI: 10.1110/ps.04672604

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  31 in total

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2.  A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm.

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Journal:  Nucleic Acids Res       Date:  2001-01-01       Impact factor: 16.971

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Journal:  Curr Opin Struct Biol       Date:  2001-06       Impact factor: 6.809

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  32 in total

1.  On the unyielding hydrophobic core of villin headpiece.

Authors:  Jeffrey W Brown; Jeremiah D Farelli; C James McKnight
Journal:  Protein Sci       Date:  2012-03-30       Impact factor: 6.725

2.  Novel protein folds and their nonsequential structural analogs.

Authors:  Aysam Guerler; Ernst-Walter Knapp
Journal:  Protein Sci       Date:  2008-06-26       Impact factor: 6.725

3.  Rapid search for tertiary fragments reveals protein sequence-structure relationships.

Authors:  Jianfu Zhou; Gevorg Grigoryan
Journal:  Protein Sci       Date:  2014-12-31       Impact factor: 6.725

4.  The SALAMI protein structure search server.

Authors:  Thomas Margraf; Gundolf Schenk; Andrew E Torda
Journal:  Nucleic Acids Res       Date:  2009-05-22       Impact factor: 16.971

5.  GIS: a comprehensive source for protein structure similarities.

Authors:  Aysam Guerler; Ernst-Walter Knapp
Journal:  Nucleic Acids Res       Date:  2010-05-11       Impact factor: 16.971

6.  Discrimination of thermophilic and mesophilic proteins.

Authors:  Todd J Taylor; Iosif I Vaisman
Journal:  BMC Struct Biol       Date:  2010-05-17

7.  Molecular model of the microvillar cytoskeleton and organization of the brush border.

Authors:  Jeffrey W Brown; C James McKnight
Journal:  PLoS One       Date:  2010-02-24       Impact factor: 3.240

8.  Striking similarities in diverse telomerase proteins revealed by combining structure prediction and machine learning approaches.

Authors:  Jae-Hyung Lee; Michael Hamilton; Colin Gleeson; Cornelia Caragea; Peter Zaback; Jeffry D Sander; Xue Li; Feihong Wu; Michael Terribilini; Vasant Honavar; Drena Dobbs
Journal:  Pac Symp Biocomput       Date:  2008

9.  Conopeptide ρ-TIA defines a new allosteric site on the extracellular surface of the α1B-adrenoceptor.

Authors:  Lotten Ragnarsson; Ching-I Anderson Wang; Åsa Andersson; Dewi Fajarningsih; Thea Monks; Andreas Brust; K Johan Rosengren; Richard J Lewis
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10.  MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments.

Authors:  Shintaro Minami; Kengo Sawada; George Chikenji
Journal:  BMC Bioinformatics       Date:  2013-01-18       Impact factor: 3.169

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