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3D Protein Structure Matching by Patch Signatures

  • Zi Huang
  • Xiaofang Zhou
  • Heng Tao Shen
  • Dawei Song
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)

Abstract

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zi Huang
    • 1
    • 2
  • Xiaofang Zhou
    • 1
    • 2
  • Heng Tao Shen
    • 1
  • Dawei Song
    • 3
  1. 1.School of ITEEThe University of QueenslandAustralia
  2. 2.Australian Research Council Centre in BioinformaticsAustralia
  3. 3.Knowledge Media Institute & Centre for Research in ComputingThe Open UniversityUnited Kingdom

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