未经证实:甲型流感病毒属于研究最多的病毒,其突变体引发了流行病和大流行。接种是降低感染风险的重要基础。为了防止流感的传播,各种实际方法需要更多的进步和进步。必须付出更多的努力和研究来提高疫苗的效力。
UNASSIGNED:本研究强调流感病毒通用疫苗的开发和扩展。研究重点是高效疫苗的设计。在这项研究中,使用了许多计算方法,涵盖了生物信息学方法论中广泛的元素和思想。来自神经氨酸酶蛋白N1的各种B和T细胞表位肽被这些方法识别。随着大量获得的数据库和生物信息学工具的实施,分析了N1神经氨酸酶保守序列的不同免疫框架方法。采用NCBI数据库检索氨基酸序列。神经氨酸酶序列的抗原性质是通过VaxiJen服务器和Kolaskar和Tongaonkar方法实现的。在筛选各种B和T细胞表位后,评估了一种来自B细胞表位和T细胞表位的有效肽的抗原决定簇疫苗功效。当使用B细胞表位预测服务器分析时,从N1蛋白识别相同的两个B细胞表位。在ABCPred和免疫表位数据库的帮助下实现了用于解释B和T细胞表位的氨基酸序列的详细检查。
UNASSIGNED:通过免疫信息学研究的计算免疫学显示出RPNDKTG具有很高的保护效率,并被证明是一种良好的抗原性,可接近的表面亲水性B细胞表位。在T细胞表位分析中,选择YVNISNTNF作为保守表位。还分析了T细胞表位的变应原性和细胞毒性评价。发现YVNISNTNF表位是非变应原,并且对细胞也没有毒性。仔细检查了具有最大世界人口覆盖率的该T细胞表位与HLA-DRB1*0401分子的关联。对接模拟分析结果显示YVNISNTNF具有较低的结合能,回转半径(Rg),RMSD值,和RMSE值,使蛋白质结构更稳定,并增加其成为流感病毒疫苗表位肽的能力。
UNASSIGNED:我们提出,在流感疫苗的年度设计中,这种表位分析可以成功地用作突变株之间的抗原-抗体反应的鲁棒性的测量工具。
UNASSIGNED: Influenza A virus belongs to the most studied virus and its mutant initiates epidemic and pandemics outbreaks. Inoculation is the significant foundation to diminish the risk of infection. To prevent an incidence of influenza from the transmission, various practical approaches require more advancement and progress. More efforts and research must take in front to enhance vaccine efficacy.
UNASSIGNED: The present research emphasizes the development and expansion of a universal vaccine for the influenza virus. Research focuses on vaccine design with high efficacy. In this study, numerous computational approaches were used, covering a wide range of elements and ideas in bioinformatics methodology. Various B and T-cell epitopic peptides derived from the Neuraminidase protein N1 are recognized by these approaches. With the implementation of numerous obtained databases and bioinformatics tools, the different immune framework methods of the conserved sequences of N1 neuraminidase were analyzed. NCBI databases were employed to retrieve amino acid sequences. The antigenic nature of the neuraminidase sequence was achieved by the VaxiJen server and Kolaskar and Tongaonkar method. After screening of various B and T cell epitopes, one efficient peptide each from B cell epitope and T cell epitopes was assessed for their antigenic determinant vaccine efficacy. Identical two B cell epitopes were recognized from the N1 protein when analyzed using B-cell epitope prediction servers. The detailed examination of amino acid sequences for interpretation of B and T cell epitopes was achieved with the help of the ABCPred and Immune Epitope Database.
UNASSIGNED: Computational immunology via immunoinformatic study exhibited RPNDKTG as having its high conservancy efficiency and demonstrated as a good antigenic, accessible surface hydrophilic B-cell epitope. Among T cell epitope analysis, YVNISNTNF was selected for being a conserved epitope. T cell epitope was also analyzed for its allergenicity and cytotoxicity evaluation. YVNISNTNF epitope was found to be a non-allergen and not toxic for cells as well. This T-cell epitope with maximum world populace coverages was scrutinized for its association with the HLA-DRB1*0401 molecule. Results from docking simulation analyses showed YVNISNTNF having lower binding energy, the radius of gyration (Rg), RMSD values, and RMSE values which make the protein structure more stable and increase its ability to become an epitopic peptide for influenza virus vaccination.
UNASSIGNED: We propose that this epitope analysis may be successfully used as a measurement tool for the robustness of an antigen-antibody reaction between mutant strains in the annual design of the influenza vaccine.