Literature DB >> 20627698

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

Chenhua Huang1, Xiangbo Yang, Zhihong 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). Copyright 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20627698     DOI: 10.1016/j.compbiolchem.2010.04.002

Source DB:  PubMed          Journal:  Comput Biol Chem        ISSN: 1476-9271            Impact factor:   2.877


  8 in total

1.  Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model.

Authors:  Changjun Zhou; Caixia Hou; Qiang Zhang; Xiaopeng Wei
Journal:  J Mol Model       Date:  2013-07-04       Impact factor: 1.810

2.  Improving coarse-grained models of protein folding through weighting of polar-polar/hydrophobic-hydrophobic interactions into crowded spaces.

Authors:  Hiram Isaac Beltrán; Salomón J Alas-Guardado; Pedro Pablo González-Pérez
Journal:  J Mol Model       Date:  2022-03-09       Impact factor: 1.810

Review 3.  Finding the needle in the haystack: towards solving the protein-folding problem computationally.

Authors:  Bian Li; Michaela Fooksa; Sten Heinze; Jens Meiler
Journal:  Crit Rev Biochem Mol Biol       Date:  2017-10-04       Impact factor: 8.250

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

Authors:  Shih-Chieh Su; Cheng-Jian Lin; Chuan-Kang Ting
Journal:  Proteome Sci       Date:  2011-10-14       Impact factor: 2.480

5.  A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences.

Authors:  Jyh-Jong Tsay; Shih-Chieh Su; Chin-Sheng Yu
Journal:  Int J Mol Sci       Date:  2015-07-03       Impact factor: 5.923

6.  An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets.

Authors:  Jyh-Jong Tsay; Shih-Chieh Su
Journal:  Proteome Sci       Date:  2013-11-07       Impact factor: 2.480

7.  Protein folding prediction in the HP model using ions motion optimization with a greedy algorithm.

Authors:  Cheng-Hong Yang; Kuo-Chuan Wu; Yu-Shiun Lin; Li-Yeh Chuang; Hsueh-Wei Chang
Journal:  BioData Min       Date:  2018-08-08       Impact factor: 2.522

8.  Searching the Optimal Folding Routes of a Complex Lasso Protein.

Authors:  Claudio Perego; Raffaello Potestio
Journal:  Biophys J       Date:  2019-06-07       Impact factor: 4.033

  8 in total

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