Fast similarity search for protein 3D structures using topological pattern matching based on spatial relations.
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 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.
Park
Sung-Hee
SH
Database Bioinformatics Laboratory, School of Electrical & Computer Engineering, Chungbuk National University, Cheongju, 361-763, Korea. shpark@dblab.chungbuk.ac.kr
Ryu
Keun Ho
KH
Gilbert
David
D
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D030562:Databases, Protein; D006801:Humans; D011487:Protein Conformation; D011506:Proteins / Q000502:physiology*; D012680:Sensitivity and Specificity; D012984:Software
D011506:Proteins