Bioinformatics Advance Access originally published online on July 29, 2004
Bioinformatics 2004 20(18):3500-3507; doi:10.1093/bioinformatics/bth435
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Bioinformatics vol. 20 issue 18 © Oxford University Press 2004; all rights reserved.
Exploring protein fold space by secondary structure prediction using data distribution method on Grid platform
1 Distributed and Mobile Computing Laboratory, Graduate School of Information and Communication, Ajou University, Suwon 442-749, Korea and 2 Biomolecular NMR Laboratory, Department of Biochemistry, Yonsei University, Seoul 120-749, Korea
Received on January 10, 2004; revised on June 21, 2004; accepted on July 17, 2004
Advance Access Publication July 29, 2004
Motivation: Since the newly developed Grid platform has been considered as a powerful tool to share resources in the Internet environment, it is of interest to demonstrate an efficient methodology to process massive biological data on the Grid environments at a low cost. This paper presents an efficient and economical method based on a Grid platform to predict secondary structures of all proteins in a given organism, which normally requires a long computation time through sequential execution, by means of processing a large amount of protein sequence data simultaneously. From the prediction results, a genome scale protein fold space can be pursued.
Results: Using the improved Grid platform, the secondary structure prediction on genomic scale and protein topology derived from the new scoring scheme for four different model proteomes was presented. This protein fold space was compared with structures from the Protein Data Bank, database and it showed similarly aligned distribution. Therefore, the fold space approach based on this new scoring scheme could be a guideline for predicting a folding family in a given organism.
Contact: wlee{at}spin.yonsei.ac.kr
* To whom correspondence should be addressed.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.