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Protein Structure Comparison Based on a Measure of Information Discrepancy

  • Zi-Kai Wu
  • Yong Wang
  • En-Min Feng
  • Jin-Cheng Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3959)

Abstract

Protein structure comparison is an important tool to explore and understand the different aspects of protein 3D structures. In this paper, a novel representation of protein structure (complete information set of C α C α distances, CISD) is formulated at first. Then an FDOD score scheme is developed to measure the similarity between two representations. Numerical experiments of the new method are conducted in four different protein datasets and clustering analyses are given to verify the effectiveness of this new similarity measure. Furthermore, preliminary results of detecting homologous protein pairs of an existing non-redundant subset of CATH v2.5.1 based on the new similarity are given as a pilot study. All the results show that this new approach to measure the similarities between protein structures is simple to implement, computationally efficient and fast.

Keywords

Root Mean Square Deviation Protein Dataset Score Scheme Protein Structure Comparison Subsequence Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zi-Kai Wu
    • 1
  • Yong Wang
    • 2
    • 3
  • En-Min Feng
    • 1
  • Jin-Cheng Zhao
    • 4
  1. 1.Department of Applied MathematicsDalian University of TechnologyDalianP.R. China
  2. 2.Institude of Applied MathematicsAcademy of Mathematics and System SciencesCAS, BeijingP.R. China
  3. 3.Osaka Sangyo UniversityDaito, OsakaJapan
  4. 4.Institute of Bioinformatics and Molecular DesignDalian UniversityDalianP.R. China

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