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Conference Paper
Fast Protein Structure Alignment Algorithm Based on Local Geometric Similarity
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- Authors
- Chan Yong Park, Sung Hee Park, Dae Hee Kim, Soo Jun Park, Man Kyu Sung, Hong Ro Lee, Jung Sub Shin, Chi Jung Hwang
- Issue Date
- 2006-11
- Citation
- Mexican International Conference on Artificial Intelligence (MICAI) 2006 (LNCS 4293), v.4293, pp.1179-1189
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper proposes a novel fast protein structure alignment algorithm and its application. Because it is known that the functions of protein are derived from its structure, the method of measuring the structural similarities between two proteins can be used to infer their functional closeness. In this paper, we propose a 3D chain code representation for fast measuring the local geometric similarity of protein and introduce a backtracking algorithm for joining a similar local substructure efficiently. A 3D chain code, which is a sequence of the directional vectors between the atoms in a protein, represents a local similarity of protein. After constructing a pair of similar substructures by referencing local similarity, we perform the protein alignment by joining the similar substructure pair through a backtracking algorithm. This method has particular advantages over all previous approaches; our 3D chain code representation is more intuitive and our experiments prove that the backtracking algorithm is faster than dynamic programming in general case. We have designed and implemented a protein structure alignment system based on our protein visualization software (MoleView). These experiments show rapid alignment with precise results. © Springer-Verlag Berlin Heidelberg 2006.
- KSP Keywords
- Alignment algorithm, Backtracking algorithm, Chain code, Geometric similarity, Protein Structure Alignment, Structure Similarity Index measure(SSIM), Visualization software, dynamic Programming, local similarity