Protein folding simulations of 2D HP model by the genetic algorithm based on optimal secondary structures

Computational Biology and Chemistry
Chenhua HuangZhihong He

Abstract

In this paper, based on the evolutionary Monte Carlo (EMC) algorithm, we have made four points of ameliorations and propose a so-called genetic algorithm based on optimal secondary structure (GAOSS) method to predict efficiently the protein folding conformations in the two-dimensional hydrophobic-hydrophilic (2D HP) model. Nine benchmarks are tested to verify the effectiveness of the proposed approach and the results show that for the listed benchmarks GAOSS can find the best solutions so far. It means that reasonable, effective and compact secondary structures (SSs) can avoid blind searches and can reduce time consuming significantly. On the other hand, as examples, we discuss the diversity of protein GSC for the 24-mer and 85-mer sequences. Several GSCs have been found by GAOSS and some of the conformations are quite different from each other. It would be useful for the designing of protein molecules. GAOSS would be an efficient tool for the protein structure predictions (PSP).

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Citations

Jul 5, 2013·Journal of Molecular Modeling·Changjun ZhouXiaopeng Wei
Jul 8, 2015·International Journal of Molecular Sciences·Jyh-Jong TsayChin-Sheng Yu
Nov 28, 2015·FEBS Letters·Thanh NguyenAbbas Khosravi
May 4, 2012·Computational Biology and Chemistry·Jingfa LiuYonglei Yao
Oct 1, 2013·Computational Biology and Chemistry·Jingfa LiuWeibo Huang
Feb 9, 2017·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Pedro P González-PérezSalomón J Alas
Mar 14, 2017·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Cheng-Hong YangHsueh-Wei Chang
Oct 5, 2017·Critical Reviews in Biochemistry and Molecular Biology·Bian LiJens Meiler
Nov 9, 2011·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Jingfa LiuJun Yu

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