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An algorithm for finding maximal common subtopologies in a set of protein structures

I Koch1, T Lengauer, E Wanke

  • 1Institute for Algorithms and Scientific Computing SCAI.ALG, GMD--German National Research Center for Information Technology, Sankt Augustin, Germany.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 1, 1996
PubMed
Summary

This study introduces a novel graph-based algorithm for identifying common substructures in protein data. The method efficiently finds connected subtopologies, improving protein structure comparison and classification.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Graph Theory

Background:

  • Comparing protein structures is crucial for understanding protein function and evolution.
  • Identifying common substructures aids in motif discovery and protein classification.

Purpose of the Study:

  • To develop a new algorithm for finding maximal common substructures in protein structures.
  • To represent protein secondary structure topology using labeled undirected graphs.

Main Methods:

  • Representing protein secondary structure topology as an undirected labeled graph.
  • Adapting the Bron-Kerbosch algorithm to enumerate maximal cliques.
  • Restricting the search to connected subtopologies to enhance efficiency.

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Main Results:

  • A novel, fast algorithm for identifying common subtopologies in protein structures.
  • Significant reduction in computational complexity compared to existing graph-theoretical methods.
  • Demonstrated efficiency and superiority in handling large protein datasets.

Conclusions:

  • The proposed graph-based algorithm offers an efficient and superior method for protein structure comparison.
  • This approach enhances the analysis of protein structures, motif definition, and classification.
  • The algorithm's ability to handle large proteins opens new avenues for structural bioinformatics research.