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Evaluating Protein Similarity from Coarse Structures
October-December 2009 (vol. 6 no. 4)
pp. 583-593
Yong Wang, Chinese Academy of Sciences, Beijing
Ling-Yun Wu, Chinese Academy of Sciences, Beijing
Ji-Hong Zhang, Beijing Foreign Studies University, Beijing
Zhong-Wei Zhan, China Aerospace Engineering Consultation Center, China
Xiang-Sun Zhang, Chinese Academy of Sciences, Beijing
Luonan Chen, Osaka Sangyo University, Osaka
To unscramble the relationship between protein function and protein structure, it is essential to assess the protein similarity from different aspects. Although many methods have been proposed for protein structure alignment or comparison, alternative similarity measures are still strongly demanded due to the requirement of fast screening and query in large-scale structure databases. In this paper, we first formulate a novel representation of a protein structure, i.e., Feature Sequence of Surface (FSS). Then, a new score scheme is developed to measure the similarity between two representations. To verify the proposed method, numerical experiments are conducted in four different protein data sets. We also classify SARS coronavirus to verify the effectiveness of the new method. Furthermore, preliminary results of fast classification of the whole CATH v2.5.1 database based on the new macrostructure similarity are given as a pilot study. We demonstrate that the proposed approach to measure the similarities between protein structures is simple to implement, computationally efficient, and surprisingly fast. In addition, the method itself provides a new and quantitative tool to view a protein structure.

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Index Terms:
Protein structure, structure comparison, protein surface.
Citation:
Yong Wang, Ling-Yun Wu, Ji-Hong Zhang, Zhong-Wei Zhan, Xiang-Sun Zhang, Luonan Chen, "Evaluating Protein Similarity from Coarse Structures," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 6, no. 4, pp. 583-593, Oct.-Dec. 2009, doi:10.1109/TCBB.2007.70250
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