3D protein structure matching by patch signatures

Huang, Zi, Zhou, Xiaofang, Shen, Heng Tao and Song, Dawei (2006). 3D protein structure matching by patch signatures. In: Stéphane Bressan, Josef Kung and Roland Wagner, Proceedings. Lecture Notes in Computer Science 4080: 17th International Conference on Database and Expert Systems Applications (DEXA 2006). 17th International Conference on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, (528-537). 4-8 September, 2006. doi:10.1007/11827405


Author Huang, Zi
Zhou, Xiaofang
Shen, Heng Tao
Song, Dawei
Title of paper 3D protein structure matching by patch signatures
Conference name 17th International Conference on Database and Expert Systems Applications (DEXA 2006)
Conference location Krakow, Poland
Conference dates 4-8 September, 2006
Proceedings title Proceedings. Lecture Notes in Computer Science 4080: 17th International Conference on Database and Expert Systems Applications (DEXA 2006)   Check publisher's open access policy
Journal name Database and Expert Systems Applications, Proceedings   Check publisher's open access policy
Place of Publication Germany
Publisher Springer-Verlag
Publication Year 2006
Sub-type Fully published paper
DOI 10.1007/11827405
ISBN 9783540378716
ISSN 0302-9743
1611-3349
Editor Stéphane Bressan
Josef Kung
Roland Wagner
Volume 4080
Start page 528
End page 537
Total pages 10
Collection year 2006
Language eng
Abstract/Summary For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have one or more matching structural regions called patches. As 3D structures for proteins are large, complex and constantly evolving, it is computationally expensive and very time-consuming to identify possible locations and sizes of patches for a given protein against a large protein database. In this paper, we address a vector space based representation for protein structures, where a patch is formed by the vectors within the region. Based on our previews work, a compact representation of the patch named patch signature is applied here. A similarity measure of two patches is then derived based on their signatures. To achieve fast patch matching in large protein databases, a match-and-expand strategy is proposed. Given a query patch, a set of small k-sized matching patches, called candidate patches, is generated in match stage. The candidate patches are further filtered by enlarging k in expand stage. Our extensive experimental results demonstrate encouraging performances with respect to this biologically critical but previously computationally prohibitive problem.
Subjects E1
280108 Database Management
700103 Information processing services
Keyword Computer Science
Theory & Methods
Alignment
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Book Series: Lecture Notes in Computer Science Book Title: Database and Expert Systems Applications

 
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Created: Thu, 23 Aug 2007, 21:54:23 EST