immunoinformatics



et al., Marwa Osman In Silico Modeling and Identification of Novel Epitopes-based Vaccine of M polyprotein (Gn/Gc) against Schmallenberg Virus for Ruminants et al., Marwa Osman In Silico Modeling and Identification of Novel Epitopes-based Vaccine of M polyprotein (Gn/Gc) against Schmallenberg Virus for Ruminants Новинка

et al., Marwa Osman In Silico Modeling and Identification of Novel Epitopes-based Vaccine of M polyprotein (Gn/Gc) against Schmallenberg Virus for Ruminants

Research Paper (postgraduate) from the year 2016 in the subject Computer Science - Bioinformatics, , language: English, abstract: Schmallenberg (SBV) is a new virus of the Bunyaviridae family within the genus Orthobunyavirus. The viral infection causes mild clinical signs: fever, reduced milk production and diarrhea, as well as considerable economic loss. There is currently no treatment or vaccine for infected animals. We aimed to design a peptide vaccine using an Immunoinformatics approach to stimulate the immune system and reduce the potentially negative effects of using live vaccines. In this study, a total of 47 strains of complete M polyprotein sequence (Gn/NSm/GC) and 61 strains of nonstructural protein in S segment (NSs) of Schmallenberg virus which were chosen for this study were taken from NCBI. Potentially continuous B and T cell epitopes were predicted using tools from immune epitope data base analysis resource (IEDB-AR). We found that Gn and Gc regions of M polyprotein in SBV were clearly suitable and could be used for the preparation of immunological constructs. Our studies suggest that: B cell epitope 764QQQACSS770 and CTL epitopes 251YMYNKYFKL259, 46SECCVKDDI54 and 234IVYVFIPIF242 could be used as a potential vaccine candidate against SBV.We consider this study distinctive because no research ever dealt with peptide-based vaccines on virulent strains of SBV using an in silico approach.

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Research Paper (postgraduate) from the year 2016 in the subject Computer Science - Bioinformatics, , language: English, abstract: Schmallenberg (SBV) is a new virus of the Bunyaviridae family within the genus Orthobunyavirus. The viral infection causes mild clinical signs: fever, reduced milk production and diarrhea, as well as considerable economic loss. There is currently no treatment or vaccine for infected animals. We aimed to design a peptide vaccine using an Immunoinformatics approach to stimulate the immune system and reduce the potentially negative effects of using live vaccines. In this study, a total of 47 strains of complete M polyprotein sequence (Gn/NSm/GC) and 61 strains of nonstructural protein in S segment (NSs) of Schmallenberg virus which were chosen for this study were taken from NCBI. Potentially continuous B and T cell epitopes were predicted using tools from immune epitope data base analysis resource (IEDB-AR). We found that Gn and Gc regions of M polyprotein in SBV were clearly suitable and could be used for the preparation of immunological constructs. Our studies suggest that: B cell epitope 764QQQACSS770 and CTL epitopes 251YMYNKYFKL259, 46SECCVKDDI54 and 234IVYVFIPIF242 could be used as a potential vaccine candidate against SBV.We consider this study distinctive because no research ever dealt with peptide-based vaccines on virulent strains of SBV using an in silico approach.
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