Protein structure abstractionand automatic clustering using secondary structure element sequences

Authors:
Sung Hee Park;Chan Yong Park;Dae Hee Kim;Seon Hee Park;Jeong Seop Sim
Affiliations:
Bioinformatics Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Bioinformatics Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Bioinformatics Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;Bioinformatics Team, Electronics and Telecommunications Research Institute, Daejeon, Korea;School of Computer Science and Engineering, Inha University, Korea
Venue:
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part II
Year:
2005

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Abstract

To study protein clustering is very important in diverse fields such as drug design and environmental industry. For a meaningful clustering, protein structure must be considered. But, protein structures are very complicated and have so much information such as angles, 3-dimensional coordinates. Thus, it is not easy to efficiently compute their relations. In this paper, we present a method to efficiently abstract and cluster protein structures using secondary structure element sequences. Since a secondary structure element sequence is an abstract representation of protein structure, it can be regarded as a useful descriptor to cluster a set of proteins at the abstraction level. Using secondary structure element sequences and their distances, we implemented an automatic protein clustering system and verify their efficiency by experimental results.