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


BACKGROUND
IPSA is publicly accessible at http://ProteinDBS.rnet.missouri.edu/IPSA.php
Chi
Pin-Hao
PH
Medical and Biological Digital Library Research Lab, Informatics Institute, University of Missouri, Columbia, MO 65211, USA.
Pang
Bin
B
Korkin
Dmitry
D
Shyu
Chi-Ren
CR
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000145:classification*; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein
D011506:Proteins