利用计算机方法鉴定SARS-CoV-2结构蛋白的表位,获得保守的合理免疫原性肽

Leonardo Pereira de Araújo , Maria Eduarda Carvalho Dias , Gislaine Cristina Scodeler , Ana de Souza Santos , Letícia Martins Soares , Patrícia Paiva Corsetti , Ana Carolina Barbosa Padovan , Nelson José de Freitas Silveira , Leonardo Augusto de Almeida
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引用次数: 3

摘要

从第一例COVID-19病例到宣布大流行之间的短时间内,开始寻找阻止SARS-CoV-2传播的方法。人们对开发能够抵抗所有变异的有效疫苗抱有很大的期望,在寻找疫苗的过程中,我们假设从SARS-CoV-2的结构成分中发现可预测的合理免疫原性肽可能有助于疫苗的研究方向。在寻找SARS-CoV-2包膜(E)、膜(M)、核衣壳(N)或刺突(S)蛋白的免疫原性肽候选物时,我们访问了全球基因组测序后每种蛋白的预测序列。我们得到了各大洲各蛋白约14441条序列的一致氨基酸序列和世界范围内的一致序列。对于与MHC-I或MHC-II相互作用和b细胞受体识别相关的每个共识结构蛋白的表位鉴定和表征,我们使用了IEDB,涉及68个E蛋白、174个M蛋白、245个N蛋白和833个S蛋白的表位。为了选择与MHC或BCR结合概率最高的表位,将每个共识序列的所有表位对齐。筛选结果显示,E、M、N和S蛋白的表位分别为1、4、8和21个。对这些抗原表位进行了计算机抗原性检测,得到16个抗原表位。对所得抗原表位进行了理化性质和致敏性评价。对结果进行排序,除了S蛋白在筛选后出现两个表位外,我们得到了每个蛋白的一个表位。为了检查每个选择的表位在蛋白质结构中的三维位置,我们使用分子同源建模。随后,通过参考MHC-I或MHC-II等位基因蛋白序列的分子对接对每个选择的表位进行评估。综上所述,本研究获得的结果表明,对SARS-CoV-2结构蛋白的推定免疫原性肽进行了合理的搜索,可以使用计算机方法改善疫苗开发。所选择的表位代表了新型冠状病毒最保守的序列,可能用于各种疫苗开发策略,因为它们也存在于所描述的SARS-CoV-2变体中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Epitope identification of SARS-CoV-2 structural proteins using in silico approaches to obtain a conserved rational immunogenic peptide

The short time between the first cases of COVID-19 and the declaration of a pandemic initiated the search for ways to stop the spread of SARS-CoV-2. There are great expectations regarding the development of effective vaccines that protect against all variants, and in the search for it, we hypothesized the obtention of a predicted rational immunogenic peptide from structural components of SARS-CoV-2 might help the vaccine research direction. In the search for a candidate of an immunogenic peptide of the SARS-CoV-2 envelope (E), membrane (M), nucleocapsid (N), or spike (S) proteins, we access the predicted sequences of each protein after the genome sequenced worldwide. We obtained the consensus amino acid sequences of about 14,441 sequences of each protein of each continent and the worldwide consensus sequence. For epitope identification and characterization from each consensus structural protein related to MHC-I or MHC-II interaction and B-cell receptor recognition, we used the IEDB reaching 68 epitopes to E, 174 to M, 245 to N, and 833 to S proteins. To select an epitope with the highest probability of binding to the MHC or BCR, all epitopes of each consensus sequence were aligned. The curation indicated 1, 4, 8, and 21 selected epitopes for E, M, N, and S proteins, respectively. Those epitopes were tested in silico for antigenicity obtaining 16 antigenic epitopes. Physicochemical properties and allergenicity evaluation of the obtained epitopes were done. Ranking the results, we obtained one epitope of each protein except for the S protein that presented two epitopes after the selection. To check the 3D position of each selected epitope in the protein structure, we used molecular homology modeling. Afterward, each selected epitope was evaluated by molecular docking to reference MHC-I or MHC-II allelic protein sequences. Taken together, the results obtained in this study showed a rational search for a putative immunogenic peptide of SARS-CoV-2 structural proteins that can improve vaccine development using in silico approaches. The epitopes selected represent the most conserved sequence of new coronavirus and may be used in a variety of vaccine development strategies since they are also presented in the described variants of SARS-CoV-2.

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Immunoinformatics (Amsterdam, Netherlands)
Immunoinformatics (Amsterdam, Netherlands) Immunology, Computer Science Applications
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