Differential epitope prediction across diverse circulating variants of SARS-COV-2 in Brazil

IF 2.6 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2024-06-29 DOI:10.1016/j.compbiolchem.2024.108139
Vanessa de Melo Cavalcanti-Dantas , Brenda Fernandes , Pedro Henrique Lopes Ferreira Dantas , Glaucielle Ramalho Uchoa , Andrei Félix Mendes , Waldecir Oliveira de Araújo Júnior , Lúcio Roberto Cançado Castellano , Ana Isabel Vieira Fernandes , Luiz Ricardo Goulart , Renato Antônio dos Santos Oliveira , Priscilla Anne Castro de Assis , Joelma Rodrigues De Souza , Clarice Neuenschwander Lins de Morais
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Abstract

COVID-19, caused by the SARS-COV-2 virus, induces numerous immunological reactions linked to the severity of the clinical condition of those infected. The surface Spike protein (S protein) present in Sars-CoV-2 is responsible for the infection of host cells. This protein presents a high rate of mutations, which can increase virus transmissibility, infectivity, and immune evasion. Therefore, we propose to evaluate, using immunoinformatic techniques, the predicted epitopes for the S protein of seven variants of Sars-CoV-2. MHC class I and II epitopes were predicted and further assessed for their immunogenicity, interferon-gamma (IFN-γ) inducing capacity, and antigenicity. For B cells, linear and structural epitopes were predicted. For class I MHC epitopes, 40 epitopes were found for the clades of Wuhan, Clade 2, Clade 3, and 20AEU.1, Gamma, and Delta, in addition to 38 epitopes for Alpha and 44 for Omicron. For MHC II, there were differentially predicted epitopes for all variants and eight equally predicted epitopes. These were evaluated for differences in the MHC II alleles to which they would bind. Regarding B cell epitopes, 16 were found in the Wuhan variant, 14 in 22AEU.1 and in Clade 3, 15 in Clade 2, 11 in Alpha and Delta, 13 in Gamma, and 9 in Omicron. When compared, there was a reduction in the number of predicted epitopes concerning the Spike protein, mainly in the Delta and Omicron variants. These findings corroborate the need for updates seen today in bivalent mRNA vaccines against COVID-19 to promote a targeted immune response to the main circulating variant, Omicron, leading to more robust protection against this virus and avoiding cases of reinfection. When analyzing the specific epitopes for the RBD region of the spike protein, the Omicron variant did not present a B lymphocyte epitope from position 390, whereas the epitope at position 493 for MHC was predicted only for the Alpha, Gamma, and Omicron variants.

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巴西 SARS-COV-2 不同循环变体的表位预测差异。
由萨斯-COV-2 病毒引起的 COVID-19 会诱发多种免疫反应,这些反应与感染者临床症状的严重程度有关。SARS-CoV-2 病毒的表面穗状蛋白(S 蛋白)负责感染宿主细胞。这种蛋白的变异率很高,会增加病毒的传播性、感染性和免疫逃避性。因此,我们建议使用免疫形式化技术评估 Sars-CoV-2 七种变体的 S 蛋白的预测表位。我们预测了 MHC I 类和 II 类表位,并进一步评估了它们的免疫原性、γ 干扰素(IFN-γ)诱导能力和抗原性。对于 B 细胞,预测了线性表位和结构表位。对于 I 类 MHC 表位,发现武汉支系、2 支系、3 支系和 20AEU.1、γ 和δ 支系有 40 个表位,此外,α 支系有 38 个表位,Ω 支系有 44 个表位。对于 MHC II,所有变体都有不同的预测表位,还有 8 个相同的预测表位。对这些表位进行了评估,以确定与之结合的 MHC II 等位基因是否存在差异。关于 B 细胞表位,武汉变体中发现了 16 个,22AEU.1 和支系 3 中发现了 14 个,支系 2 中发现了 15 个,Alpha 和 Delta 中发现了 11 个,Gamma 中发现了 13 个,Omicron 中发现了 9 个。相比之下,有关 Spike 蛋白的预测表位数量有所减少,主要是在 Delta 和 Omicron 变体中。这些发现证实,目前针对 COVID-19 的二价 mRNA 疫苗需要更新,以促进对主要流行变体 Omicron 的靶向免疫反应,从而对这种病毒提供更强大的保护,避免再次感染。在分析尖峰蛋白 RBD 区的特异性表位时,Omicron 变体在 390 位没有出现 B 淋巴细胞表位,而 MHC 的 493 位表位只在 Alpha、Gamma 和 Omicron 变体中出现。
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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