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Prediction of neddylation sites from protein sequences and sequence-derived properties
BACKGROUND: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheim...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682398/ https://www.ncbi.nlm.nih.gov/pubmed/26679222 http://dx.doi.org/10.1186/1471-2105-16-S18-S9 |
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author | Yavuz, Ahmet Sinan Sözer, Namık Berk Sezerman, Osman Uğur |
author_facet | Yavuz, Ahmet Sinan Sözer, Namık Berk Sezerman, Osman Uğur |
author_sort | Yavuz, Ahmet Sinan |
collection | PubMed |
description | BACKGROUND: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheimer's and cancer. Therefore, understanding the neddylation mechanism and determining neddylation targets possibly bears a huge importance in further understanding the cellular processes. This study is the first attempt to predict neddylated sites from protein sequences by using several sequence and sequence-based structural features. RESULTS: We have developed a neddylation site prediction method using a support vector machine based on various sequence properties, position-specific scoring matrices, and disorder. Using 21 amino acid long lysine-centred windows, our model was able to predict neddylation sites successfully, with an average 5-fold stratified cross validation performance of 0.91, 0.91, 0.75, 0.44, 0.95 for accuracy, specificity, sensitivity, Matthew's correlation coefficient and area under curve, respectively. Independent test set results validated the robustness of reported new method. Additionally, we observed that neddylation sites are commonly flexible and there is a significant positively charged amino acid presence in neddylation sites. CONCLUSIONS: In this study, a neddylation site prediction method was developed for the first time in literature. Common characteristics of neddylation sites and their discriminative properties were explored for further in silico studies on neddylation. Lastly, up-to-date neddylation dataset was provided for researchers working on post-translational modifications in the accompanying supplementary material of this article. |
format | Online Article Text |
id | pubmed-4682398 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46823982015-12-21 Prediction of neddylation sites from protein sequences and sequence-derived properties Yavuz, Ahmet Sinan Sözer, Namık Berk Sezerman, Osman Uğur BMC Bioinformatics Research BACKGROUND: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheimer's and cancer. Therefore, understanding the neddylation mechanism and determining neddylation targets possibly bears a huge importance in further understanding the cellular processes. This study is the first attempt to predict neddylated sites from protein sequences by using several sequence and sequence-based structural features. RESULTS: We have developed a neddylation site prediction method using a support vector machine based on various sequence properties, position-specific scoring matrices, and disorder. Using 21 amino acid long lysine-centred windows, our model was able to predict neddylation sites successfully, with an average 5-fold stratified cross validation performance of 0.91, 0.91, 0.75, 0.44, 0.95 for accuracy, specificity, sensitivity, Matthew's correlation coefficient and area under curve, respectively. Independent test set results validated the robustness of reported new method. Additionally, we observed that neddylation sites are commonly flexible and there is a significant positively charged amino acid presence in neddylation sites. CONCLUSIONS: In this study, a neddylation site prediction method was developed for the first time in literature. Common characteristics of neddylation sites and their discriminative properties were explored for further in silico studies on neddylation. Lastly, up-to-date neddylation dataset was provided for researchers working on post-translational modifications in the accompanying supplementary material of this article. BioMed Central 2015-12-09 /pmc/articles/PMC4682398/ /pubmed/26679222 http://dx.doi.org/10.1186/1471-2105-16-S18-S9 Text en Copyright © 2015 Yavuz et al.; 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 Yavuz, Ahmet Sinan Sözer, Namık Berk Sezerman, Osman Uğur Prediction of neddylation sites from protein sequences and sequence-derived properties |
title | Prediction of neddylation sites from protein sequences and sequence-derived properties |
title_full | Prediction of neddylation sites from protein sequences and sequence-derived properties |
title_fullStr | Prediction of neddylation sites from protein sequences and sequence-derived properties |
title_full_unstemmed | Prediction of neddylation sites from protein sequences and sequence-derived properties |
title_short | Prediction of neddylation sites from protein sequences and sequence-derived properties |
title_sort | prediction of neddylation sites from protein sequences and sequence-derived properties |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682398/ https://www.ncbi.nlm.nih.gov/pubmed/26679222 http://dx.doi.org/10.1186/1471-2105-16-S18-S9 |
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