Journal article
Smolign: A Spatial Motifs-Based Protein Multiple Structural Alignment Method
IEEE/ACM transactions on computational biology and bioinformatics, v 9(1)
Jan 2012
PMID: 21464513
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences mostly through pairwise comparison of consecutive fragments, which can lead to suboptimal alignments, especially when the similarity among the proteins is low. We introduce a novel strategy based on: building a contact-window based motif library from the protein structural data, discovery and extension of common alignment seeds from this library, and optimal superimposition of multiple structures according to these alignment seeds by an enhanced partial order curve comparison method. The ability of our strategy to detect multiple correspondences simultaneously, to catch alignments globally, and to support flexible alignments, endorse a sensitive and robust automated algorithm that can expose similarities among protein structures even under low similarity conditions. Our method yields better alignment results compared to other popular MSTA methods, on several protein structure data sets that span various structural folds and represent different protein similarity levels. A web-based alignment tool, a downloadable executable, and detailed alignment results for the data sets used here are available at http://sacan.biomed. drexel.edu/Smolign and http://bio.cse.ohio-state.edu/Smolign.
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Details
- Title
- Smolign: A Spatial Motifs-Based Protein Multiple Structural Alignment Method
- Creators
- Hong Sun - The Ohio State University, ColumbusAhmet Sacan - Drexel University, PhiladelphiaHakan Ferhatosmanoglu - The Ohio State University, ColumbusYusu Wang - The Ohio State University, Columbus
- Publication Details
- IEEE/ACM transactions on computational biology and bioinformatics, v 9(1)
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000296782200021
- Scopus ID
- 2-s2.0-84875629516
- Other Identifier
- 991014877833904721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biochemical Research Methods
- Computer Science, Interdisciplinary Applications
- Mathematics, Interdisciplinary Applications
- Statistics & Probability