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SEPPA: a computational server for spatial epitope prediction of protein antigens
In recent years, a lot of efforts have been made in conformational epitope prediction as antigen proteins usually bind antibodies with an assembly of sequentially discontinuous and structurally compact surface residues. Currently, only a few methods for spatial epitope prediction are available with...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703964/ https://www.ncbi.nlm.nih.gov/pubmed/19465377 http://dx.doi.org/10.1093/nar/gkp417 |
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author | Sun, Jing Wu, Di Xu, Tianlei Wang, Xiaojing Xu, Xiaolian Tao, Lin Li, Y. X. Cao, Z. W. |
author_facet | Sun, Jing Wu, Di Xu, Tianlei Wang, Xiaojing Xu, Xiaolian Tao, Lin Li, Y. X. Cao, Z. W. |
author_sort | Sun, Jing |
collection | PubMed |
description | In recent years, a lot of efforts have been made in conformational epitope prediction as antigen proteins usually bind antibodies with an assembly of sequentially discontinuous and structurally compact surface residues. Currently, only a few methods for spatial epitope prediction are available with focus on single residue propensity scales or continual segments clustering. In the method of SEPPA, a concept of ‘unit patch of residue triangle’ was introduced to better describe the local spatial context in protein surface. Besides that, SEPPA incorporated clustering coefficient to describe the spatial compactness of surface residues. Validated by independent testing datasets, SEPPA gave an average AUC value over 0.742 and produced a successful pick-up rate of 96.64%. Comparing with peers, SEPPA shows significant improvement over other popular methods like CEP, DiscoTope and BEpro. In addition, the threshold scores for certain accuracy, sensitivity and specificity are provided online to give the confidence level of the spatial epitope identification. The web server can be accessed at http://lifecenter.sgst.cn/seppa/index.php. Batch query is supported. |
format | Text |
id | pubmed-2703964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27039642009-07-01 SEPPA: a computational server for spatial epitope prediction of protein antigens Sun, Jing Wu, Di Xu, Tianlei Wang, Xiaojing Xu, Xiaolian Tao, Lin Li, Y. X. Cao, Z. W. Nucleic Acids Res Articles In recent years, a lot of efforts have been made in conformational epitope prediction as antigen proteins usually bind antibodies with an assembly of sequentially discontinuous and structurally compact surface residues. Currently, only a few methods for spatial epitope prediction are available with focus on single residue propensity scales or continual segments clustering. In the method of SEPPA, a concept of ‘unit patch of residue triangle’ was introduced to better describe the local spatial context in protein surface. Besides that, SEPPA incorporated clustering coefficient to describe the spatial compactness of surface residues. Validated by independent testing datasets, SEPPA gave an average AUC value over 0.742 and produced a successful pick-up rate of 96.64%. Comparing with peers, SEPPA shows significant improvement over other popular methods like CEP, DiscoTope and BEpro. In addition, the threshold scores for certain accuracy, sensitivity and specificity are provided online to give the confidence level of the spatial epitope identification. The web server can be accessed at http://lifecenter.sgst.cn/seppa/index.php. Batch query is supported. Oxford University Press 2009-07-01 2009-05-22 /pmc/articles/PMC2703964/ /pubmed/19465377 http://dx.doi.org/10.1093/nar/gkp417 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Sun, Jing Wu, Di Xu, Tianlei Wang, Xiaojing Xu, Xiaolian Tao, Lin Li, Y. X. Cao, Z. W. SEPPA: a computational server for spatial epitope prediction of protein antigens |
title | SEPPA: a computational server for spatial epitope prediction of protein antigens |
title_full | SEPPA: a computational server for spatial epitope prediction of protein antigens |
title_fullStr | SEPPA: a computational server for spatial epitope prediction of protein antigens |
title_full_unstemmed | SEPPA: a computational server for spatial epitope prediction of protein antigens |
title_short | SEPPA: a computational server for spatial epitope prediction of protein antigens |
title_sort | seppa: a computational server for spatial epitope prediction of protein antigens |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703964/ https://www.ncbi.nlm.nih.gov/pubmed/19465377 http://dx.doi.org/10.1093/nar/gkp417 |
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