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Protein Folding Prediction Using an Improved Genetic-Annealing Algorithm

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AI 2006: Advances in Artificial Intelligence (AI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4304))

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Abstract

Based on the off-lattice AB model consisting of hydrophobic and hydrophilic residues, a novel hybrid algorithm is presented for searching the ground-state conformation of the protein. This algorithm combines genetic algorithm and simulated annealing. A kind of optimization of the crossover operators in the genetic algorithm is implemented, where a local adjustment mechanism is used to enhance the searching ability for optimal solutions of the off-lattice AB model. Experimental results demonstrate that the proposed algorithm is feasible and can insure the solution quality when used to search for native states with off-lattice AB model.

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Authors and Affiliations

  1. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, P.R. China

    Xiaolong Zhang & Xiaoli Lin

Authors
  1. Xiaolong Zhang
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  2. Xiaoli Lin
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Editor information

Editors and Affiliations

  1. DisPRR, National ICT Australia Ltd, QLD, Australia

    Abdul Sattar

  2. School of Computing, University of Tasmania, Sandy Bay, 7005, Tasmania, Australia

    Byeong-ho Kang

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, X., Lin, X. (2006). Protein Folding Prediction Using an Improved Genetic-Annealing Algorithm. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_147

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  • DOI: https://doi.org/10.1007/11941439_147

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49787-5

  • Online ISBN: 978-3-540-49788-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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