An effective hybrid of hill climbing and genetic algorithm for 2D triangular protein structure prediction

Proteome Science

Proceedings

Cheng-Jian Lin¹  Chuan-Kang Ting²  Shih-Chieh Su² 

[1] Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, 41101, Taichung, Taiwan, R.O.C;Department of Computer Science and Information Engineering, National Chung Cheng University, 62102, Chiayi, Taiwan, R.O.C;

关键词: Genetic Algorithm;    Local Search;    Free Energy;    Lattice Model;    Triangular Lattice;   

DOI  :  10.1186/1477-5956-9-S1-S19

来源: Springer

【 摘 要 】

BackgroundProteins play fundamental and crucial roles in nearly all biological processes, such as, enzymatic catalysis, signaling transduction, DNA and RNA synthesis, and embryonic development. It has been a long-standing goal in molecular biology to predict the tertiary structure of a protein from its primary amino acid sequence. From visual comparison, it was found that a 2D triangular lattice model can give a better structure modeling and prediction for proteins with short primary amino acid sequences.MethodsThis paper proposes a hybrid of hill-climbing and genetic algorithm (HHGA) based on elite-based reproduction strategy for protein structure prediction on the 2D triangular lattice.ResultsThe simulation results show that the proposed HHGA can successfully deal with the protein structure prediction problems. Specifically, HHGA significantly outperforms conventional genetic algorithms and is comparable to the state-of-the-art method in terms of free energy.ConclusionsThanks to the enhancement of local search on the global search, the proposed HHGA achieves promising results on the 2D triangular protein structure prediction problem. The satisfactory simulation results demonstrate the effectiveness of the proposed HHGA and the utility of the 2D triangular lattice model for protein structure prediction.

【 授权许可】

Unknown   
© Su et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.