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Article Abstract

Title: Protein cavity clustering based on community structure of pocket similarity network
  Author: Zhi-Ping Liu, Ling-Yun Wu, Yong Wang, Xiang-Sun Zhang, Luonan Chen   Email author(s)
  Address: Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China. ' Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. ' Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. ' Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. ' Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, Osaka 574-8530, Japan; Institute of Systems Biology, Shanghai University, Shanghai 200044, China
  Journal: International Journal of Bioinformatics Research and Applications 2008 - Vol. 4, No.4  pp. 445 - 460
  Abstract: Functions of a protein are mainly determined by its structure. Surface cavities, also called pockets or clefts, are ordinarily regarded as potentially active sites where the protein carries out the functions. Clustering these pockets is a challenging task in structural genomics. In this paper, we introduce pocket similarity network which possesses the feature of community structure to systematically describe structural similarity among pockets, then a straightforward classification scheme is developed based on this special feature. The surface pockets are clustered into structurally similar pocket groups via a hierarchical process. We identify these small pocket groups as structural templates which represent similar functions in diverse proteins. The experimental results show that our clustering method is effective, and the identified pocket groups are biologically meaningful in terms of their functional features.
  Keywords: protein surface pattern; protein cavity clustering; pocket similarity network; structural motif; functional genomics; bioinformatics; surface cavities; classification.
  DOI: 10.1504/IJBRA.2008.021179
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