基于刺突糖蛋白保守序列的新型SARS-CoV-2多表位亚单位疫苗的免疫信息学设计

I. Ekaidem, A. Moses, Y. Tatfeng
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引用次数: 2

摘要

Sars-CoV-2感染也被称为COVID-19,其特征是发烧和急性呼吸窘迫综合征(ARDS)的迹象。它目前是一种全球大流行病,重症患者的死亡率很高。缺乏有效的疫苗和经批准的治疗药物在全球社区造成了灾难性的状况。这项研究是在基于蛋白质的亚单位疫苗开发的道路上向前迈出的一步。利用SARS-CoV-2刺突糖蛋白一级氨基酸序列设计蛋白质亚单位疫苗结构。该疫苗蛋白分子量为58.4 kDa,共有8170个原子,584个氨基酸残基。理论pI为8.54,显示其微碱性,带正电残基总数分别为29个和33个。该肽疫苗结构有147个(25.17%)极性残基和375个(64.21%)疏水残基。该疫苗结构具有不同长度的细胞毒性T淋巴细胞(CTL)、辅助性T淋巴细胞(HTL)和B细胞表位,具有刺激高水平IFN-γ产生的巨大潜力。它具有强效的抗原性,但缺乏致敏性。它稳定,对TLR-4受体具有良好的结合亲和力。总的来说,该模型按顺序应用了一系列免疫信息学工具,以找到可有效用于对抗COVID-19大流行的有效疫苗。然而,这种建模需要实际的实验验证,以证明计算工作的可操作性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Immunoinformatics Design of Novel Multi-Epitope Subunit Vaccine for SARS-CoV-2 by Exploring Virus Conserved Sequences of the Spike Glycoproteins
Sars-CoV-2 infection also called COVID-19 is characterized by fever and signs of acute respiratory distress syndrome (ARDS). It is currently a global pandemic with high mortality rate in those with severe disease. Lack of effective vaccine and approved drug for treatment created a disastrous condition among the global communities. This study was designed as a step ahead in the path of protein-based subunit vaccine development. The primary amino acid sequence of SARS-CoV-2 spike glycoprotein was used to design a protein subunit vaccine construct. The molecular weight of vaccine protein was 58.4 kDa with a total number of 8170 atoms and 584 amino acid residues. The theoretical pI was found to be 8.54 showing its slightly basic nature while the total number of negative and positive charged residues were 29 and 33 respectively. The peptide vaccine construct has 147 (25.17%) polar residues and 375 (64.21%) hydrophobic residues. The vaccine construct has cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell epitopes of varying lengths having great potential to stimulate high levels of IFN-γ production. It has potent antigenic properties but lacked allergenicity. It is stable and have a good binding affinity for the TLR-4 receptor. In general, this modelling applied a series of immunoinformatics tools in a sequential manner to find an effective vaccine that may be used effectively in fighting against the COVID-19 pandemic. This modelling, however, needs real life experimental validation to prove the workability of the computational work.
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