Constraint-Based Evolutionary Local Search for Protein Structures with Secondary Motifs

  • Swakkhar Shatabda
  • M. A. Hakim Newton
  • Abdul Sattar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8862)


On-lattice protein structure prediction with empirical energy minimisation has drawn significant research effort. However, energy minimisation with free-modelling not necessarily leads to structures that are similar to the native structure of the given protein. In this paper, we show that energy minimisation has a positive correlation with structural similarity measures if we consider secondary motifs. We then present a constraint-based evolutionary local search framework for on-lattice protein structure prediction using secondary structural information. We approximate secondary motifs such as α-helix and β-strands on the lattice and propose a set of neighbourhood generation operators that respect those motifs. Our experimental results show significant improvement over the state-of-the-art methods in terms of similarity with the native structures determined by laboratory methods.


Local Search Protein Structure Prediction Face Centered Cubic Free Modelling Local Search Phase 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Swakkhar Shatabda
    • 1
    • 2
  • M. A. Hakim Newton
    • 2
  • Abdul Sattar
    • 1
    • 2
  1. 1.Queensland Research LabNational ICT AustraliaAustralia
  2. 2.Institute for Integrated & Intelligent SystemsGriffith UniversityAustralia

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