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Development of MHC class nonamers from Cowpea mosaic viral protein

机译：利用Cow豆花叶病毒蛋白开发MHC类九聚体

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Cowpea mosaic virus causes one of the most commonly reported virus diseases of cowpea (Vigna unguiculata), in which it produces chlorotic spots with diffuse borders in inoculated primary leaves. Cowpea mosaic viral peptides are most suitable for subunit vaccine development because with single epitope, the immune response can be generated in large population. Peptide binders identified through this approach tend to high-efficiency binders, which is lagers percentage of their atoms are directly involved in binding as compared to larger molecules. For development of MHC binder prediction method, an elegant machine learning technique support vector machine (SVM) has been used. SVM has been trained on the binary input of single amino acid sequence. We also found the SVM based MHCII-IAb peptide regions 51-PTINHPTFV, 113-PLPKFDSTV, 187-VYSKDDALE, 181- RKYAVLVYS, (optimal score is 1.034); MHCII-IAd peptide regions 138-AISAMFADG, 170-LSAMRADIG, 25- PSSADANFR, 191-DDALETDEL, (optimal score is 0.541); MHCII-IAg7 peptide regions 27-SADANFRVL, 151- LVYQYAASG, 159-GVQANNKLL, 158-SGVQANNKL, (optimal score is 1.692); and MHCII- RT1.B peptide regions 57-TFVGSERCR, 188-YSKDDALET, 68-YTFTSITLK, 44-KTLAAGRPT, (optimal score is 0.787) which represented predicted binders from genome polyprotein m. These antigenic epitope are sufficient for eliciting the desired immune response against viral infection. Study focused on computational approach to deciphering the peptide fragments, which are antigenic in nature for synthetic peptides viral vaccines and their function of genome polyprotein m. In analysis predicted antigenic epitopes of genome polyprotein m are predicted a successful immunization strategy against various diseases.
机译：pea豆花叶病毒是引起reported豆（Vigna unguiculata）最常见的病毒病之一，在该病中，接种的初生叶会产生带有弥散边界的褪绿斑点。 pea豆花叶病毒肽最适合亚单位疫苗的开发，因为具有单个表位的免疫反应可在大量人群中产生。通过这种方法鉴定出的肽结合剂趋向于高效结合剂，与较大分子相比，其原子的滞后百分比直接参与结合。为了开发MHC结合剂预测方法，已经使用了优雅的机器学习技术支持向量机（SVM）。 SVM已在单个氨基酸序列的二进制输入上受过训练。我们还发现基于SVM的MHCII-IAb肽区域51-PTINHPTFV，113-PLPKFDSTV，187-VYSKDDALE，181-RKYAVLVYS（最佳评分为1.034）; MHCII-IAd肽区域138-AISAMFADG，170-LSAMRADIG，25-PSSADANFR，191-DDALETDEL（最佳分数为0.541）; MHCII-IAg7肽区域27-SADANFRVL，151-LVYQYAASG，159-GVQANNKLL，158-SGVQANNKL（最佳分数为1.692）; MHCII-RT1.B和MHCII-RT1.B肽区域57-TFVGSERCR，188-YSKDDALET，68-YTFTSITLK，44-KTLAAGRPT（最佳分数为0.787），其代表来自基因组多蛋白m的预测结合物。这些抗原表位足以引发针对病毒感染的所需免疫反应。研究重点在于解密肽片段的计算方法，该肽片段本质上对合成肽病毒疫苗具有抗原性，并具有基因组多蛋白m的功能。在分析中，预测了基因组多蛋白m的预期抗原表位是针对各种疾病的成功免疫策略。

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