BACKGROUND: Norovirus is the major cause of nonbacterial epidemic gastroenteritis, being highly prevalent in both developing and developed countries. Despite of the available monoclonal antibodies (MAbs) for different sub-genogroups, a comprehensive epitope analysis based on various bioinformatics technology is highly desired for future potential antibody development in clinical diagonosis and treatment. METHODS: A total of 18 full-length human norovirus capsid protein sequences were downloaded from GenBank. Protein modeling was performed with program Modeller 9.9. The modeled 3D structures of capsid protein of norovirus were submitted to the protein antigen spatial epitope prediction webserver (SEPPA) for predicting the possible spatial epitopes with the default threshold. The results were processed using the Biosoftware. RESULTS: Compared with GI, we found that the GII genogroup had four deletions and two special insertions in the VP1 region. The predicted conformational epitope regions mainly concentrated on N-terminal (1~96), Middle Part (298~305, 355~375) and C-terminal (560~570). We find two common epitope regions on sequences for GI and GII genogroup, and also found an exclusive epitope region for GII genogroup. CONCLUSIONS: The predicted conformational epitope regions of norovirus VP1 mainly concentrated on N-terminal, Middle Part and C-terminal. We find two common epitope regions on sequences for GI and GII genogroup, and also found an exclusive epitope region for GII genogroup. The overlapping with experimental epitopes indicates the important role of latest computational technologies. With the fast development of computational immunology tools, the bioinformatics pipeline will be more and more critical to vaccine design.
BACKGROUND: Norovirus is the major cause of nonbacterial epidemic gastroenteritis, being highly prevalent in both developing and developed countries. Despite of the available monoclonal antibodies (MAbs) for different sub-genogroups, a comprehensive epitope analysis based on various bioinformatics technology is highly desired for future potential antibody development in clinical diagonosis and treatment. METHODS: A total of 18 full-length human norovirus capsid protein sequences were downloaded from GenBank. Protein modeling was performed with program Modeller 9.9. The modeled 3D structures of capsid protein of norovirus were submitted to the protein antigen spatial epitope prediction webserver (SEPPA) for predicting the possible spatial epitopes with the default threshold. The results were processed using the Biosoftware. RESULTS: Compared with GI, we found that the GII genogroup had four deletions and two special insertions in the VP1 region. The predicted conformational epitope regions mainly concentrated on N-terminal (1~96), Middle Part (298~305, 355~375) and C-terminal (560~570). We find two common epitope regions on sequences for GI and GII genogroup, and also found an exclusive epitope region for GII genogroup. CONCLUSIONS: The predicted conformational epitope regions of norovirus VP1 mainly concentrated on N-terminal, Middle Part and C-terminal. We find two common epitope regions on sequences for GI and GII genogroup, and also found an exclusive epitope region for GII genogroup. The overlapping with experimental epitopes indicates the important role of latest computational technologies. With the fast development of computational immunology tools, the bioinformatics pipeline will be more and more critical to vaccine design.
Authors: A D Hale; T N Tanaka; N Kitamoto; M Ciarlet; X Jiang; N Takeda; D W Brown; M K Estes Journal: J Clin Microbiol Date: 2000-04 Impact factor: 5.948
Authors: T Yoda; Y Terano; Y Suzuki; K Yamazaki; I Oishi; T Kuzuguchi; H Kawamoto; E Utagawa; K Takino; H Oda; T Shibata Journal: BMC Microbiol Date: 2001-10-08 Impact factor: 3.605
Authors: Zhang Hong-ying; Shi Li-min; Li Wei; Wang Xuan; Qiao Meng-kai; He Min; Wang Yan; Xie Guo-xiang Journal: Biomed Res Int Date: 2014-07-15 Impact factor: 3.411
Authors: Yongqun He; Zhiwei Cao; Anne S De Groot; Vladimir Brusic; Christian Schönbach; Nikolai Petrovsky Journal: BMC Bioinformatics Date: 2013-03-08 Impact factor: 3.169