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A Similarity Search Algorithm to Predict Protein Structures

  • Jiyuan An
  • Yi-Ping Phoebe Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

Accurate prediction of protein structures is very important for many applications such as drug discovery and biotechnology. Building side chains is an essential to get any reliable prediction of the protein structure for any given a protein main chain conformation. Most of the methods that predict side chain conformations use statistically generated data from known protein structures. It is a computationally intractable problem to search suitable side chains from all possible rotamers simultaneously using information of known protein structures. Reducing the number of possibility is a main issue to predict side chain conformation. This paper proposes an enumeration based similarity search algorithm to predict side chain conformations. By introducing “beam search” technique, a significant number of unrelated side chain rotamers can easily be eliminated. As a result, we can search for suitable residue side chains from all possible side chain conformations.

Keywords

Amino Acid Residue Discriminatory Function Atom Type Beam Search Rotamer Library 
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

  • Jiyuan An
    • 1
  • Yi-Ping Phoebe Chen
    • 1
    • 2
  1. 1.School of Information TechnologyDeakin UniversityAustralia
  2. 2.Australian Research Council Centre in Bioinformatics 

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