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Bioinformatics Advance Access originally published online on August 10, 2009
Bioinformatics 2009 25(19):2559-2565; doi:10.1093/bioinformatics/btp474
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Efficient SCOP-fold classification and retrieval using index-based protein substructure alignments

Pin-Hao Chi 1,2, Bin Pang 1,2, Dmitry Korkin 1,2 and Chi-Ren Shyu 1,2,*

1Medical and Biological Digital Library Research Lab, Informatics Institute and 2Department of Computer Science, University of Missouri, Columbia, MO 65211, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: To investigate structure–function relationships, life sciences researchers usually retrieve and classify proteins with similar substructures into the same fold. A manually constructed database, SCOP, is believed to be highly accurate; however, it is labor intensive. Another known method, DALI, is also precise but computationally expensive. We have developed an efficient algorithm, namely, index-based protein substructure alignment (IPSA), for protein-fold classification. IPSA constructs a two-layer indexing tree to quickly retrieve similar substructures in proteins and suggests possible folds by aligning these substructures.

Results: Compared with known algorithms, such as DALI, CE, MultiProt and MAMMOTH, on a sample dataset of non-redundant proteins from SCOP v1.73, IPSA exhibits an efficiency improvement of 53.10, 16.87, 3.60 and 1.64 times speedup, respectively. Evaluated on three different datasets of non-redundant proteins from SCOP, average accuracy of IPSA is approximately equal to DALI and better than CE, MAMMOTH, MultiProt and SSM. With reliable accuracy and efficiency, this work will benefit the study of high-throughput protein structure–function relationships.

Availability: IPSA is publicly accessible at http://ProteinDBS.rnet.missouri.edu/IPSA.php

Contact: ShyuC{at}missouri.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Anna Tramontano

Received on March 31, 2009; revised on July 7, 2009; accepted on July 24, 2009

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