Literature DB >> 24838566

SEPPA 2.0--more refined server to predict spatial epitope considering species of immune host and subcellular localization of protein antigen.

Tao Qi1, Tianyi Qiu2, Qingchen Zhang1, Kailin Tang3, Yangyang Fan1, Jingxuan Qiu1, Dingfeng Wu1, Wei Zhang1, Yanan Chen1, Jun Gao4, Ruixin Zhu1, Zhiwei Cao5.   

Abstract

Spatial Epitope Prediction server for Protein Antigens (SEPPA) has received lots of feedback since being published in 2009. In this improved version, relative ASA preference of unit patch and consolidated amino acid index were added as further classification parameters in addition to unit-triangle propensity and clustering coefficient which were previously reported. Then logistic regression model was adopted instead of the previous simple additive one. Most importantly, subcellular localization of protein antigen and species of immune host were fully taken account to improve prediction. The result shows that AUC of 0.745 (5-fold cross-validation) is almost the baseline performance with no differentiation like all the other tools. Specifying subcellular localization of protein antigen and species of immune host will generally push the AUC up. Secretory protein immunized to mouse can push AUC to 0.823. In this version, the false positive rate has been largely decreased as well. As the first method which has considered the subcellular localization of protein antigen and species of immune host, SEPPA 2.0 shows obvious advantages over the other popular servers like SEPPA, PEPITO, DiscoTope-2, B-pred, Bpredictor and Epitopia in supporting more specific biological needs. SEPPA 2.0 can be accessed at http://badd.tongji.edu.cn/seppa/. Batch query is also supported.
© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2014        PMID: 24838566      PMCID: PMC4086087          DOI: 10.1093/nar/gku395

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  17 in total

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Review 2.  Immunodominance: a pivotal principle in host response to viral infections.

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3.  Prediction of residues in discontinuous B-cell epitopes using protein 3D structures.

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5.  Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature.

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Authors:  Urmila Kulkarni-Kale; Shriram Bhosle; A S Kolaskar
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7.  SEPPA: a computational server for spatial epitope prediction of protein antigens.

Authors:  Jing Sun; Di Wu; Tianlei Xu; Xiaojing Wang; Xiaolian Xu; Lin Tao; Y X Li; Z W Cao
Journal:  Nucleic Acids Res       Date:  2009-05-22       Impact factor: 16.971

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  15 in total

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3.  Conformational epitope matching and prediction based on protein surface spiral features.

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Review 5.  Progress and challenges in predicting protein interfaces.

Authors:  Reyhaneh Esmaielbeiki; Konrad Krawczyk; Bernhard Knapp; Jean-Christophe Nebel; Charlotte M Deane
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Journal:  J Gen Virol       Date:  2015-01-22       Impact factor: 3.891

7.  Incorporating structure context of HA protein to improve antigenicity calculation for influenza virus A/H3N2.

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10.  A novel B- and helper T-cell epitopes-based prophylactic vaccine against Echinococcus granulosus.

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