{"product_id":"in-silico-modeling-and-identification-et-al-9783668335295","title":"In Silico Modeling and Identification of Novel Epitopes-based Vaccine of M polyprotein (Gn\/Gc) against Schmallenberg Virus for Ruminants","description":"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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Et Al,Marwa Osman\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 366833529X\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9783668335295\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Grin Verlag\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 12\/07\/2016\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 36\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.13lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 8.27h x 5.83w x 0.09d","brand":"Et Al","offers":[{"title":"Paperback","offer_id":48217638109439,"sku":"9783668335295","price":40.9,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_45325ddb-b794-42a3-a40a-52c058a3714b.jpg?v=1771998482","url":"https:\/\/www.whiterainbookhouse.com\/products\/in-silico-modeling-and-identification-et-al-9783668335295","provider":"WR Book House","version":"1.0","type":"link"}