Title
Protein cavity clustering based on community structure of pocket similarity network
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.
Year
DOI
Venue
2008
10.1504/IJBRA.2008.021179
IJBRA
Keywords
Field
DocType
community structure,functional genomics,bioinformatics,structural motif,classification
Community structure,Structural genomics,Biology,Classification scheme,Functional genomics,Structural similarity,Structural motif,Template,Bioinformatics,Cluster analysis
Journal
Volume
Issue
Citations 
4
4
2
PageRank 
References 
Authors
0.37
8
5
Name
Order
Citations
PageRank
Zhi-Ping Liu11008.99
Ling-yun Wu245626.67
Yong Wang357546.58
Xiang-Sun Zhang4101677.06
Luonan Chen51485145.71