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Protein domain identification methods and online resources

Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, over the past two decad...

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Detalles Bibliográficos
Autores principales: Wang, Yan, Zhang, Hang, Zhong, Haolin, Xue, Zhidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7895673/
https://www.ncbi.nlm.nih.gov/pubmed/33680357
http://dx.doi.org/10.1016/j.csbj.2021.01.041
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author Wang, Yan
Zhang, Hang
Zhong, Haolin
Xue, Zhidong
author_facet Wang, Yan
Zhang, Hang
Zhong, Haolin
Xue, Zhidong
author_sort Wang, Yan
collection PubMed
description Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, over the past two decades, a number of protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, namely sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods.
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spelling pubmed-78956732021-03-04 Protein domain identification methods and online resources Wang, Yan Zhang, Hang Zhong, Haolin Xue, Zhidong Comput Struct Biotechnol J Review Article Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, over the past two decades, a number of protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, namely sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods. Research Network of Computational and Structural Biotechnology 2021-02-02 /pmc/articles/PMC7895673/ /pubmed/33680357 http://dx.doi.org/10.1016/j.csbj.2021.01.041 Text en © 2021 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Wang, Yan
Zhang, Hang
Zhong, Haolin
Xue, Zhidong
Protein domain identification methods and online resources
title Protein domain identification methods and online resources
title_full Protein domain identification methods and online resources
title_fullStr Protein domain identification methods and online resources
title_full_unstemmed Protein domain identification methods and online resources
title_short Protein domain identification methods and online resources
title_sort protein domain identification methods and online resources
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7895673/
https://www.ncbi.nlm.nih.gov/pubmed/33680357
http://dx.doi.org/10.1016/j.csbj.2021.01.041
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