A hybrid clustering of protein binding sites

被引:10
|
作者
Ivan, Gabor [1 ,2 ]
Szabadka, Zoltan [1 ,2 ]
Grolmusz, Vince [1 ,2 ]
机构
[1] Eotvos Lorand Univ, Dept Comp Sci, Prot Informat Technol Grp, H-1117 Budapest, Hungary
[2] Uratim Ltd, Budapest, Hungary
基金
匈牙利科学研究基金会;
关键词
binding sites; clustering; distance; OPTICS; PDB; sequence; FUNCTIONAL CLASSIFICATION; SEQUENCE; PREDICTION; DATABASE; MOTIFS; PFAM;
D O I
10.1111/j.1742-4658.2010.07578.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The Protein Data Bank contains the description of approximately 27 000 protein-ligand binding sites. Most of the ligands at these sites are biologically active small molecules, affecting the biological function of the protein. The classification of their binding sites may lead to relevant results in drug discovery and design. Clusters of similar binding sites were created here by a hybrid, sequence and spatial structure-based approach, using the OPTICS clustering algorithm. A dissimilarity measure was defined: a distance function on the amino acid sequences of the binding sites. All the binding sites were clustered in the Protein Data Bank according to this distance function, and it was found that the clusters characterized well the Enzyme Commission numbers of the entries. The results, carefully color coded by the Enzyme Commission numbers of the proteins, containing the 20 967 binding sites clustered, are available as html files in three parts at http://pitgroup.org/seqclust/.
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页码:1494 / 1502
页数:9
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