Nucleic Acids Research Advance Access published online on November 26, 2007
Nucleic Acids Research, doi:10.1093/nar/gkm1049
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Methods Online |
STRALCP—structure alignment-based clustering of proteins
1Computing Applications and Research, Lawrence Livermore National Laboratory, Livermore, CA 94550 and 2Division of Cell Biology and Biophysics, University of Missouri-Kansas City, Kansas City, MO 64110, USA
*To whom correspondence should be addressed. Tel: +1 925 4235571; Fax: +1 925 4236437; Email: adamz{at}llnl.gov
Received June 11, 2007. Revised October 14, 2007. Accepted November 6, 2007.
Protein structural annotation and classification is an important and challenging problem in bioinformatics. Research towards analysis of sequence–structure correspondences is critical for better understanding of a protein's structure, function, and its interaction with other molecules. Clustering of protein domains based on their structural similarities provides valuable information for protein classification schemes. In this article, we attempt to determine whether structure information alone is sufficient to adequately classify protein structures. We present an algorithm that identifies regions of structural similarity within a given set of protein structures, and uses those regions for clustering. In our approach, called STRALCP (STRucture ALignment-based Clustering of Proteins), we generate detailed information about global and local similarities between pairs of protein structures, identify fragments (spans) that are structurally conserved among proteins, and use these spans to group the structures accordingly. We also provide a web server at http://as2ts.llnl.gov/AS2TS/STRALCP/ for selecting protein structures, calculating structurally conserved regions and performing automated clustering.