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Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features

BACKGROUND: Secondary structures prediction of proteins is important to many protein structure modeling applications. Correct prediction of secondary structures can significantly reduce the degrees of freedom in protein tertiary structure modeling and therefore reduces the difficulty of obtaining hi...

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Detalles Bibliográficos
Autores principales: Yaseen, Ashraf, Li, Yaohang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120151/
https://www.ncbi.nlm.nih.gov/pubmed/25080939
http://dx.doi.org/10.1186/1471-2105-15-S8-S3
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author Yaseen, Ashraf
Li, Yaohang
author_facet Yaseen, Ashraf
Li, Yaohang
author_sort Yaseen, Ashraf
collection PubMed
description BACKGROUND: Secondary structures prediction of proteins is important to many protein structure modeling applications. Correct prediction of secondary structures can significantly reduce the degrees of freedom in protein tertiary structure modeling and therefore reduces the difficulty of obtaining high resolution 3D models. METHODS: In this work, we investigate a template-based approach to enhance 8-state secondary structure prediction accuracy. We construct structural templates from known protein structures with certain sequence similarity. The structural templates are then incorporated as features with sequence and evolutionary information to train two-stage neural networks. In case of structural templates absence, heuristic structural information is incorporated instead. RESULTS: After applying the template-based 8-state secondary structure prediction method, the 7-fold cross-validated Q8 accuracy is 78.85%. Even templates from structures with only 20%~30% sequence similarity can help improve the 8-state prediction accuracy. More importantly, when good templates are available, the prediction accuracy of less frequent secondary structures, such as 3-10 helices, turns, and bends, are highly improved, which are useful for practical applications. CONCLUSIONS: Our computational results show that the templates containing structural information are effective features to enhance 8-state secondary structure predictions. Our prediction algorithm is implemented on a web server named "C8-SCORPION" available at: http://hpcr.cs.odu.edu/c8scorpion.
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spelling pubmed-41201512014-08-11 Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features Yaseen, Ashraf Li, Yaohang BMC Bioinformatics Research BACKGROUND: Secondary structures prediction of proteins is important to many protein structure modeling applications. Correct prediction of secondary structures can significantly reduce the degrees of freedom in protein tertiary structure modeling and therefore reduces the difficulty of obtaining high resolution 3D models. METHODS: In this work, we investigate a template-based approach to enhance 8-state secondary structure prediction accuracy. We construct structural templates from known protein structures with certain sequence similarity. The structural templates are then incorporated as features with sequence and evolutionary information to train two-stage neural networks. In case of structural templates absence, heuristic structural information is incorporated instead. RESULTS: After applying the template-based 8-state secondary structure prediction method, the 7-fold cross-validated Q8 accuracy is 78.85%. Even templates from structures with only 20%~30% sequence similarity can help improve the 8-state prediction accuracy. More importantly, when good templates are available, the prediction accuracy of less frequent secondary structures, such as 3-10 helices, turns, and bends, are highly improved, which are useful for practical applications. CONCLUSIONS: Our computational results show that the templates containing structural information are effective features to enhance 8-state secondary structure predictions. Our prediction algorithm is implemented on a web server named "C8-SCORPION" available at: http://hpcr.cs.odu.edu/c8scorpion. BioMed Central 2014-07-14 /pmc/articles/PMC4120151/ /pubmed/25080939 http://dx.doi.org/10.1186/1471-2105-15-S8-S3 Text en Copyright © 2014 Yaseen and Li; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), 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
Yaseen, Ashraf
Li, Yaohang
Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title_full Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title_fullStr Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title_full_unstemmed Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title_short Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features
title_sort template-based c8-scorpion: a protein 8-state secondary structure prediction method using structural information and context-based features
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120151/
https://www.ncbi.nlm.nih.gov/pubmed/25080939
http://dx.doi.org/10.1186/1471-2105-15-S8-S3
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