SEPPA: A computational server for spatial epitope prediction of protein antigens

Jing Sun, Di Wu, Tianlei Xu, Xiaojing Wang, Xiaolian Xu, Lin Tao, Y. X. Li, Z. W. Cao

Research output: Contribution to journalArticlepeer-review

132 Scopus citations


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 Batch query is supported.

Original languageEnglish (US)
Pages (from-to)W612-W616
JournalNucleic acids research
Issue numberSUPPL. 2
StatePublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Genetics


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