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SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens

B-cell epitope information is critical to immune therapy and vaccine design. Protein epitopes can be significantly affected by glycosylation, while no methods have considered this till now. Based on previous versions of Spatial Epitope Prediction of Protein Antigens (SEPPA), we here present an enhan...

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Detalles Bibliográficos
Autores principales: Zhou, Chen, Chen, Zikun, Zhang, Lu, Yan, Deyu, Mao, Tiantian, Tang, Kailin, Qiu, Tianyi, Cao, Zhiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602482/
https://www.ncbi.nlm.nih.gov/pubmed/31114919
http://dx.doi.org/10.1093/nar/gkz413
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author Zhou, Chen
Chen, Zikun
Zhang, Lu
Yan, Deyu
Mao, Tiantian
Tang, Kailin
Qiu, Tianyi
Cao, Zhiwei
author_facet Zhou, Chen
Chen, Zikun
Zhang, Lu
Yan, Deyu
Mao, Tiantian
Tang, Kailin
Qiu, Tianyi
Cao, Zhiwei
author_sort Zhou, Chen
collection PubMed
description B-cell epitope information is critical to immune therapy and vaccine design. Protein epitopes can be significantly affected by glycosylation, while no methods have considered this till now. Based on previous versions of Spatial Epitope Prediction of Protein Antigens (SEPPA), we here present an enhanced tool SEPPA 3.0, enabling glycoprotein antigens. Parameters were updated based on the latest and largest dataset. Then, additional micro-environmental features of glycosylation triangles and glycosylation-related amino acid indexes were added as important classifiers, coupled with final calibration based on neighboring antigenicity. Logistic regression model was retained as SEPPA 2.0. The AUC value of 0.794 was obtained through 10-fold cross-validation on internal validation. Independent testing on general protein antigens resulted in AUC of 0.740 with BA (balanced accuracy) of 0.657 as baseline of SEPPA 3.0. Most importantly, when tested on independent glycoprotein antigens only, SEPPA 3.0 gave an AUC of 0.749 and BA of 0.665, leading the top performance among peers. As the first server enabling accurate epitope prediction for glycoproteins, SEPPA 3.0 shows significant advantages over popular peers on both general protein and glycoprotein antigens. It can be accessed at http://bidd2.nus.edu.sg/SEPPA3/ or at http://www.badd-cao.net/seppa3/index.html. Batch query is supported.
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spelling pubmed-66024822019-07-05 SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens Zhou, Chen Chen, Zikun Zhang, Lu Yan, Deyu Mao, Tiantian Tang, Kailin Qiu, Tianyi Cao, Zhiwei Nucleic Acids Res Web Server Issue B-cell epitope information is critical to immune therapy and vaccine design. Protein epitopes can be significantly affected by glycosylation, while no methods have considered this till now. Based on previous versions of Spatial Epitope Prediction of Protein Antigens (SEPPA), we here present an enhanced tool SEPPA 3.0, enabling glycoprotein antigens. Parameters were updated based on the latest and largest dataset. Then, additional micro-environmental features of glycosylation triangles and glycosylation-related amino acid indexes were added as important classifiers, coupled with final calibration based on neighboring antigenicity. Logistic regression model was retained as SEPPA 2.0. The AUC value of 0.794 was obtained through 10-fold cross-validation on internal validation. Independent testing on general protein antigens resulted in AUC of 0.740 with BA (balanced accuracy) of 0.657 as baseline of SEPPA 3.0. Most importantly, when tested on independent glycoprotein antigens only, SEPPA 3.0 gave an AUC of 0.749 and BA of 0.665, leading the top performance among peers. As the first server enabling accurate epitope prediction for glycoproteins, SEPPA 3.0 shows significant advantages over popular peers on both general protein and glycoprotein antigens. It can be accessed at http://bidd2.nus.edu.sg/SEPPA3/ or at http://www.badd-cao.net/seppa3/index.html. Batch query is supported. Oxford University Press 2019-07-02 2019-05-22 /pmc/articles/PMC6602482/ /pubmed/31114919 http://dx.doi.org/10.1093/nar/gkz413 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Zhou, Chen
Chen, Zikun
Zhang, Lu
Yan, Deyu
Mao, Tiantian
Tang, Kailin
Qiu, Tianyi
Cao, Zhiwei
SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title_full SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title_fullStr SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title_full_unstemmed SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title_short SEPPA 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
title_sort seppa 3.0—enhanced spatial epitope prediction enabling glycoprotein antigens
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602482/
https://www.ncbi.nlm.nih.gov/pubmed/31114919
http://dx.doi.org/10.1093/nar/gkz413
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