Literature DB >> 17473323

Multiple graph alignment for the structural analysis of protein active sites.

Nils Weskamp1, Eyke Hüllermeier, Daniel Kuhn, Gerhard Klebe.   

Abstract

Graphs are frequently used to describe the geometry and also the physicochemical composition of protein active sites. Here, the concept of graph alignment as a novel method for the structural analysis of protein binding pockets is presented. Using inexact graph-matching techniques, one is able to identify both conserved areas and regions of difference among different binding pockets. Thus, using multiple graph alignments, it is possible to characterize functional protein families and to examine differences among related protein families independent of sequence or fold homology. Optimized algorithms are described for the efficient calculation of multiple graph alignments for the analysis of physicochemical descriptors representing protein binding pockets. Additionally, it is shown how the calculated graph alignments can be analyzed to identify structural features that are characteristic for a given protein family and also features that are discriminative among related families. The methods are applied to a substantial high-quality subset of the PDB database and their ability to successfully characterize and classify 10 highly populated functional protein families is shown. Additionally, two related protein families from the group of serine proteases are examined and important structural differences are detected automatically and efficiently.

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Year:  2007        PMID: 17473323     DOI: 10.1109/tcbb.2007.358301

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  3 in total

1.  A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction.

Authors:  Brice Hoffmann; Mikhail Zaslavskiy; Jean-Philippe Vert; Véronique Stoven
Journal:  BMC Bioinformatics       Date:  2010-02-22       Impact factor: 3.169

2.  Alignments of biomolecular contact maps.

Authors:  Peter F Stadler
Journal:  Interface Focus       Date:  2021-06-11       Impact factor: 4.661

3.  Proteins comparison through probabilistic optimal structure local alignment.

Authors:  Giovanni Micale; Alfredo Pulvirenti; Rosalba Giugno; Alfredo Ferro
Journal:  Front Genet       Date:  2014-09-02       Impact factor: 4.599

  3 in total

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