PSIST: Indexing Protein Structures Using Suffix Trees
CSB '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference
PSIST: A scalable approach to indexing protein structures using suffix trees
Journal of Parallel and Distributed Computing
Graph algorithms for biological systems analysis
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
FlexSnap: flexible non-sequential protein structure alignment
WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
ISBRA'10 Proceedings of the 6th international conference on Bioinformatics Research and Applications
A parameterized algorithm for protein structure alignment
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
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Motivation: Proteins of the same class often share a secondary structure packing arrangement but differ in how the secondary structure units are ordered in the sequence. We find that proteins that share a common core also share local sequence--structure similarities, and these can be exploited to align structures with different topologies. In this study, segments from a library of local sequence--structure alignments were assembled hierarchically, enforcing the compactness and conserved inter-residue contacts but not sequential ordering. Previous structure-based alignment methods often ignore sequence similarity, local structural equivalence and compactness. Results: The new program, SCALI (Structural Core ALIgnment), can efficiently find conserved packing arrangements, even if they are non-sequentially ordered in space. SCALI alignments conserve remote sequence similarity and contain fewer alignment errors. Clustering of our pairwise non-sequential alignments shows that recurrent packing arrangements exist in topologically different structures. For example, the three-layer sandwich domain architecture may be divided into four structural subclasses based on internal packing arrangements. These subclasses represent an intermediate level of structure classification, more general than topology, but more specific than architecture as defined in CATH. A strategy is presented for developing a set of predictive hidden Markov models based on multiple SCALI alignments. Availability: An online topology-independent SCALI structure comparison server is available at http://www.bioinfo.rpi.edu/~bystrc/scali.html Contact: bystrc@rpi.edu