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

BACKGROUND: Proteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a protein's tertiary structure based on its primary amino acid sequence has lon...

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Autores principales: Tsay, Jyh-Jong, Su, Shih-Chieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908773/
https://www.ncbi.nlm.nih.gov/pubmed/24565217
http://dx.doi.org/10.1186/1477-5956-11-S1-S19
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author Tsay, Jyh-Jong
Su, Shih-Chieh
author_facet Tsay, Jyh-Jong
Su, Shih-Chieh
author_sort Tsay, Jyh-Jong
collection PubMed
description BACKGROUND: Proteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a protein's tertiary structure based on its primary amino acid sequence has long been the most important and challenging subject in biochemistry, molecular biology and biophysics. In the past, the HP lattice model was one of the ab initio methods that many researchers used to forecast the protein structure. Although these kinds of simplified methods could not achieve high resolution, they provided a macrocosm-optimized protein structure. The model has been employed to investigate general principles of protein folding, and plays an important role in the prediction of protein structures. METHODS: In this paper, we present an improved evolutionary algorithm for the protein folding problem. We study the problem on the 3D FCC lattice HP model which has been widely used in previous research. Our focus is to develop evolutionary algorithms (EA) which are robust, easy to implement and can handle various energy functions. We propose to combine three different local search methods, including lattice rotation for crossover, K-site move for mutation, and generalized pull move; these form our key components to improve previous EA-based approaches. RESULTS: We have carried out experiments over several data sets which were used in previous research. The results of the experiments show that our approach is able to find optimal conformations which were not found by previous EA-based approaches. CONCLUSIONS: We have investigated the geometric properties of the 3D FCC lattice and developed several local search techniques to improve traditional EA-based approaches to the protein folding problem. It is known that EA-based approaches are robust and can handle arbitrary energy functions. Our results further show that by extensive development of local searches, EA can also be very effective for finding optimal conformations on the 3D FCC HP model. Furthermore, the local searches developed in this paper can be integrated with other approaches such as the Monte Carlo and Tabu searches to improve their performance.
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spelling pubmed-39087732014-02-13 An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets Tsay, Jyh-Jong Su, Shih-Chieh Proteome Sci Research BACKGROUND: Proteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a protein's tertiary structure based on its primary amino acid sequence has long been the most important and challenging subject in biochemistry, molecular biology and biophysics. In the past, the HP lattice model was one of the ab initio methods that many researchers used to forecast the protein structure. Although these kinds of simplified methods could not achieve high resolution, they provided a macrocosm-optimized protein structure. The model has been employed to investigate general principles of protein folding, and plays an important role in the prediction of protein structures. METHODS: In this paper, we present an improved evolutionary algorithm for the protein folding problem. We study the problem on the 3D FCC lattice HP model which has been widely used in previous research. Our focus is to develop evolutionary algorithms (EA) which are robust, easy to implement and can handle various energy functions. We propose to combine three different local search methods, including lattice rotation for crossover, K-site move for mutation, and generalized pull move; these form our key components to improve previous EA-based approaches. RESULTS: We have carried out experiments over several data sets which were used in previous research. The results of the experiments show that our approach is able to find optimal conformations which were not found by previous EA-based approaches. CONCLUSIONS: We have investigated the geometric properties of the 3D FCC lattice and developed several local search techniques to improve traditional EA-based approaches to the protein folding problem. It is known that EA-based approaches are robust and can handle arbitrary energy functions. Our results further show that by extensive development of local searches, EA can also be very effective for finding optimal conformations on the 3D FCC HP model. Furthermore, the local searches developed in this paper can be integrated with other approaches such as the Monte Carlo and Tabu searches to improve their performance. BioMed Central 2013-11-07 /pmc/articles/PMC3908773/ /pubmed/24565217 http://dx.doi.org/10.1186/1477-5956-11-S1-S19 Text en Copyright © 2013 Tsay and Su; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Tsay, Jyh-Jong
Su, Shih-Chieh
An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title_full An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title_fullStr An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title_full_unstemmed An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title_short An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets
title_sort effective evolutionary algorithm for protein folding on 3d fcc hp model by lattice rotation and generalized move sets
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908773/
https://www.ncbi.nlm.nih.gov/pubmed/24565217
http://dx.doi.org/10.1186/1477-5956-11-S1-S19
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