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Protein Science (2003), 12:2492-2507.
Copyright © 2003 The Protein Society

Multiple structural alignment by secondary structures: Algorithm and applications

Oranit Dror1, Hadar Benyamini2, Ruth Nussinov2,3 and Haim J. Wolfson1

1 School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences and
2 Sackler Institute of Molecular Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
3 Basic Research Program, SAIC-Frederick, Inc., Laboratory of Experimental and Computational Biology, NCI–FCRDC, Frederick, Maryland 21702, USA

Reprint requests to: Oranit Dror, School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel; e-mail: oranit{at}post.tau.ac.il; fax: 972-3-640-6476.

We present MASS (Multiple Alignment by Secondary Structures), a novel highly efficient method for structural alignment of multiple protein molecules and detection of common structural motifs. MASS is based on a two-level alignment, using both secondary structure and atomic representation. Utilizing secondary structure information aids in filtering out noisy solutions and achieves efficiency and robustness. Currently, only a few methods are available for addressing the multiple structural alignment task. In addition to using secondary structure information, the advantage of MASS as compared to these methods is that it is a combination of several important characteristics: (1) While most existing methods are based on series of pairwise comparisons, and thus might miss optimal global solutions, MASS is truly multiple, considering all the molecules simultaneously; (2) MASS is sequence order-independent and thus capable of detecting nontopological structural motifs; (3) MASS is able to detect not only structural motifs, shared by all input molecules, but also motifs shared only by subsets of the molecules. Here, we show the application of MASS to various protein ensembles. We demonstrate its ability to handle a large number (order of tens) of molecules, to detect nontopological motifs and to find biologically meaningful alignments within nonpredefined subsets of the input. In particular, we show how by using conserved structural motifs, one can guide protein–protein docking, which is a notoriously difficult problem. MASS is freely available at http://bioinfo3d.cs.tau.ac.il/MASS/.

Keywords: Multiple structural comparison; nonsequential alignment; nontopological motif; supersecondary structural motif; docking; protein structure classification; large-scale structure comparison


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