Fast similarity search for protein 3D structures using topological pattern matching based on spatial relations

被引:5
作者
Park, SH [1 ]
Ryu, KH
机构
[1] Chungbuk Natl Univ, Database Bioinformat Lab, Sch Elect & Comp Engn, Cheonju 361763, South Korea
[2] Univ Glasgow, Dept Comp Sci, Bioinformat Res Ctr, Glasgow G12 8QQ, Lanark, Scotland
关键词
similarity search; structure alignment; structure comparison; topological pattern; topology of protein;
D O I
10.1142/S0129065705000244
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Similarity search for protein 3D structures become complex and computationally expensive due to the fact that the size of protein structure databases continues to grow tremendously. Recently, fast structural similarity search systems have been required to put them into practical use in protein structure classification whilst existing comparison systems do not provide comparison results on time. Our approach uses multi-step processing that composes of a preprocessing step to represent geometry of protein structures with spatial objects, a filter step to generate a small candidate set using approximate topological string matching, and a refinement step to compute a structural alignment. This paper describes the preprocessing and filtering for fast similarity search using the discovery of topological patterns of secondary structure elements based on spatial relations. Our system is fully implemented by using Oracle 8i spatial. We have previously shown 1 that our approach has the advantage of speed of performance compared with other approach such as DALI This work shows that the discovery of topological relations of secondary structure elements in protein structures by using spatial relations of spatial databases is practical for fast structural similarity search for proteins.
引用
收藏
页码:287 / 296
页数:10
相关论文
共 28 条
[1]  
Alexandrov NN, 1996, PROTEINS, V25, P354, DOI 10.1002/(SICI)1097-0134(199607)25:3<354::AID-PROT7>3.3.CO
[2]  
2-W
[3]   Gapped BLAST and PSI-BLAST: a new generation of protein database search programs [J].
Altschul, SF ;
Madden, TL ;
Schaffer, AA ;
Zhang, JH ;
Zhang, Z ;
Miller, W ;
Lipman, DJ .
NUCLEIC ACIDS RESEARCH, 1997, 25 (17) :3389-3402
[4]   The Protein Data Bank [J].
Berman, HM ;
Westbrook, J ;
Feng, Z ;
Gilliland, G ;
Bhat, TN ;
Weissig, H ;
Shindyalov, IN ;
Bourne, PE .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :235-242
[5]   E-MSD: the European Bioinformatics Institute Macromolecular Structure Database [J].
Boutselakis, H ;
Dimitropoulos, D ;
Fillon, J ;
Golovin, A ;
Henrick, K ;
Hussain, A ;
Ionides, J ;
John, M ;
Keller, PA ;
Krissinel, E ;
McNeil, P ;
Naim, A ;
Newman, R ;
Oldfield, T ;
Pineda, J ;
Rachedi, A ;
Copeland, J ;
Sitnov, A ;
Sobhany, S ;
Suarez-Uruena, A ;
Swaminathan, J ;
Tagari, M ;
Tate, J ;
Tromm, S ;
Velankar, S ;
Vranken, W .
NUCLEIC ACIDS RESEARCH, 2003, 31 (01) :458-462
[6]   A protein structure comparison methodology [J].
Brown, NP ;
Orengo, CA ;
Taylor, WR .
COMPUTERS & CHEMISTRY, 1996, 20 (03) :359-380
[7]  
CAMOGLU O, 2003, J BIOIN, V19
[8]  
Clementini E., 1993, Advances in Spatial Databases. Third International Symposium, SSD '93 Proceedings, P277
[9]   Surprising similarities in structure comparison [J].
Gibrat, JF ;
Madej, T ;
Bryant, SH .
CURRENT OPINION IN STRUCTURAL BIOLOGY, 1996, 6 (03) :377-385
[10]   Motif-based searching in TOPS protein topology databases [J].
Gilbert, D ;
Westhead, D ;
Nagano, N ;
Thornton, J .
BIOINFORMATICS, 1999, 15 (04) :317-326