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Multi-Objective Evolutionary Algorithm NSGA-II for Protein Structure Prediction using Structural and Energetic Properties

Author

Listed:
  • R. A. Faccioli

    (Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo, Brazil)

  • L. O. Bortot

    (Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brazil)

  • A. C. B. Delbem

    (Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo, Brazil)

Abstract

The Protein Structure Prediction (PSP) problem is concerned about the prediction of the native tertiary structure of a protein in respect to its amino acids sequence. PSP is a challenging and computationally open problem. Therefore, several researches and methodologies have been developed for it. In this way, developers are working to integrate frameworks in order to improve their capabilities and make their use more straightforward. This paper presents the application of NSGA-II algorithm using structural and energetic properties of protein. The implementation of this algorithm is based on ProtPred-GROMACS (2PG), an evolutionary framework for PSP. This framework is the integration between ProtPred and GROMACS. Six proteins were used to measure the capacity of ab initio predictions. The results were interesting since in all cases the native-like topology was obtained.

Suggested Citation

  • R. A. Faccioli & L. O. Bortot & A. C. B. Delbem, 2014. "Multi-Objective Evolutionary Algorithm NSGA-II for Protein Structure Prediction using Structural and Energetic Properties," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 4(1), pages 43-53, January.
    • Handle: RePEc:igg:jncr00:v:4:y:2014:i:1:p:43-53
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