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Pelican — Protein-structure Alignment using Cellular Automaton models

  • Deepak K Gangadhar
Conference paper

Abstract

With more than 23000 protein structures deposited in the Protein Data Bank (PDB) and more structures being discovered with each passing day, the experimental determination of the 3-dimensional structure of proteins is just the beginning of a journey in-silico. For a structural biologist, this enormous surge of structural data carries with it far greater computational challenges; Compare, align, classify, and categorize them under families, domains and functionally similar proteins already discovered. Pelican provides the structural biologist with a strong and easy technique that that will help him in facing these challenges. Pelican is a rapid way to align the backbones of two protein structures using 2-dimensional Cellular Automaton (CA) models. Breaking down the protein structure into distance matrices comprising of 5 peptide units, Pelican uses the differences of these matrices to construct the 2-dimensional CA grid. Starting from an initial unaligned state, the CA evolves through several generations according to a defined set of local rules. As the CA evolves through successive generations, the emergent patterns made by the live cells are the ones that contribute to the alignment. Pelican is also an example of a system exhibiting emergent behavior. Each cell behaves in a strictly microscopic way, but each individual cell’s behavior leads to a macroscopic long range behavior exhibited by the entire system which collectively gives the alignment.

Keywords

Cellular Automaton Protein Data Bank Emergent Behavior Difference Matrix Cross Direction 
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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References

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Copyright information

© Springer-Verlag/Wien 2005

Authors and Affiliations

  • Deepak K Gangadhar
    • 1
  1. 1.IBM Software Labs (ISL), Golden EnclaveBangaloreIndia

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