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Multiple structural alignment and core detection by geometric hashing.

N Leibowitz1, Z Y Fligelman, R Nussinov

  • 1Dept. of Computer Science, School of Math. Sc., Tel Aviv University, Israel.

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|April 29, 2000
PubMed
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This study introduces a novel Multiple Structural Alignment algorithm for finding common C alpha atom substructures across protein ensembles. The efficient method simultaneously detects the core structure and performs alignment, applicable to any molecular ensemble.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Algorithm Development

Background:

  • Comparing multiple protein structures is crucial for understanding biological function and evolution.
  • Existing methods often struggle with identifying conserved core substructures efficiently across large ensembles.
  • The need for sequence-order independent alignment methods is critical for non-homologous or structurally divergent molecules.

Purpose of the Study:

  • To develop and present a novel Multiple Structural Alignment algorithm.
  • To identify the largest common C alpha atom substructure (core) present in all molecules of an ensemble.
  • To simultaneously achieve core detection and structural alignment for efficiency.

Main Methods:

  • The algorithm utilizes the Geometric Hashing paradigm.

Related Experiment Videos

  • A superimposition clustering technique represents alignments by sets of matching atoms.
  • The method processes an ensemble of protein structures to find common geometric configurations.

    • Main Results:

    • The algorithm successfully identifies the largest common C alpha atom core.
    • Simultaneous core detection and structural alignment were achieved.
    • Experiments on real data demonstrated the algorithm's efficiency.

    Conclusions:

    • The developed Multiple Structural Alignment algorithm is efficient for protein structure comparison.
    • The sequence-order independent nature allows application to diverse molecular ensembles.
    • This method provides a robust approach for identifying conserved structural cores.