GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins

Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function....

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Main Authors: Soraya Mirzaei, Jafar Razmara, Shahriar Lotfi
Format: Article
Language:English
Published: Tabriz University of Medical Sciences 2021-07-01
Series:BioImpacts
Subjects:
Online Access:https://bi.tbzmed.ac.ir/PDF/bi-11-271.pdf
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spelling doaj-eee73badd18c46bd9c8e6b560dcdd9852021-08-04T03:42:26ZengTabriz University of Medical SciencesBioImpacts2228-56602228-56522021-07-0111427127910.34172/bi.2021.37bi-22013GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteinsSoraya Mirzaei0Jafar Razmara1Shahriar Lotfi2Department of Computer Science, Faculty of Mathematics, Statistics, and Computer Science, University of Tabriz, Tabriz, IranDepartment of Computer Science, Faculty of Mathematics, Statistics, and Computer Science, University of Tabriz, Tabriz, IranDepartment of Computer Science, Faculty of Mathematics, Statistics, and Computer Science, University of Tabriz, Tabriz, IranIntroduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable. Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment. Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues. Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.https://bi.tbzmed.ac.ir/PDF/bi-11-271.pdfbioinformaticsprotein structure alignmentgenetic algorithmdynamic programming
collection DOAJ
language English
format Article
sources DOAJ
author Soraya Mirzaei
Jafar Razmara
Shahriar Lotfi
spellingShingle Soraya Mirzaei
Jafar Razmara
Shahriar Lotfi
GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
BioImpacts
bioinformatics
protein structure alignment
genetic algorithm
dynamic programming
author_facet Soraya Mirzaei
Jafar Razmara
Shahriar Lotfi
author_sort Soraya Mirzaei
title GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
title_short GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
title_full GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
title_fullStr GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
title_full_unstemmed GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins
title_sort gadp-align: a genetic algorithm and dynamic programming-based method for structural alignment of proteins
publisher Tabriz University of Medical Sciences
series BioImpacts
issn 2228-5660
2228-5652
publishDate 2021-07-01
description Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable. Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment. Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues. Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.
topic bioinformatics
protein structure alignment
genetic algorithm
dynamic programming
url https://bi.tbzmed.ac.ir/PDF/bi-11-271.pdf
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AT jafarrazmara gadpalignageneticalgorithmanddynamicprogrammingbasedmethodforstructuralalignmentofproteins
AT shahriarlotfi gadpalignageneticalgorithmanddynamicprogrammingbasedmethodforstructuralalignmentofproteins
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