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利用免疫信息学工具构建 Zika 病毒多表位疫苗的计算机模型。

In silico construction of a multiepitope Zika virus vaccine using immunoinformatics tools.

机构信息

Department of Bioscience and Technology, Institute of Tropical Pathology and Public Health, Federal University of Goiás, Rua 235 s/n, sala 335, Setor Universitário, Goiânia, GO, 74605-050, Brazil.

Departament of Master in Environmental Sciences and Health, School of Medical, Pharmaceutical and Biomedical Sciences, Pontifical Catholic University of Goiás, Goiânia, Brazil.

出版信息

Sci Rep. 2022 Jan 7;12(1):53. doi: 10.1038/s41598-021-03990-6.

Abstract

Zika virus (ZIKV) is an arbovirus from the Flaviviridae family and Flavivirus genus. Neurological events have been associated with ZIKV-infected individuals, such as Guillain-Barré syndrome, an autoimmune acute neuropathy that causes nerve demyelination and can induce paralysis. With the increase of ZIKV infection incidence in 2015, malformation and microcephaly cases in newborns have grown considerably, which suggested congenital transmission. Therefore, the development of an effective vaccine against ZIKV became an urgent need. Live attenuated vaccines present some theoretical risks for administration in pregnant women. Thus, we developed an in silico multiepitope vaccine against ZIKV. All structural and non-structural proteins were investigated using immunoinformatics tools designed for the prediction of CD4 + and CD8 + T cell epitopes. We selected 13 CD8 + and 12 CD4 + T cell epitopes considering parameters such as binding affinity to HLA class I and II molecules, promiscuity based on the number of different HLA alleles that bind to the epitopes, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the vaccine construct, creating a hybrid protein domain-multiepitope vaccine. Three high scoring continuous and two discontinuous B cell epitopes were found in EDIII. Aiming to increase the candidate vaccine antigenicity even further, we tested secondary and tertiary structures and physicochemical parameters of the vaccine conjugated to four different protein adjuvants: flagellin, 50S ribosomal protein L7/L12, heparin-binding hemagglutinin, or RS09 synthetic peptide. The addition of the flagellin adjuvant increased the vaccine's predicted antigenicity. In silico predictions revealed that the protein is a probable antigen, non-allergenic and predicted to be stable. The vaccine's average population coverage is estimated to be 87.86%, which indicates it can be administered worldwide. Peripheral Blood Mononuclear Cells (PBMC) of individuals with previous ZIKV infection were tested for cytokine production in response to the pool of CD4 and CD8 ZIKV peptide selected. CD4 + and CD8 + T cells showed significant production of IFN-γ upon stimulation and IL-2 production was also detected by CD8 + T cells, which indicated the potential of our peptides to be recognized by specific T cells and induce immune response. In conclusion, we developed an in silico universal vaccine predicted to induce broad and high-coverage cellular and humoral immune responses against ZIKV, which can be a good candidate for posterior in vivo validation.

摘要

Zika 病毒(ZIKV)是黄病毒科和黄病毒属的一种虫媒病毒。与感染 ZIKV 的个体相关的神经事件,例如吉兰-巴雷综合征,这是一种自身免疫性急性神经病,可导致神经脱髓鞘并可引起瘫痪。随着 2015 年 ZIKV 感染发病率的增加,新生儿畸形和小头畸形病例显著增加,这表明存在先天性传播。因此,开发针对 ZIKV 的有效疫苗成为当务之急。活减毒疫苗在孕妇中使用存在一些理论风险。因此,我们开发了一种针对 ZIKV 的基于计算机的多表位疫苗。使用针对 CD4+和 CD8+T 细胞表位预测设计的免疫信息学工具研究了所有结构和非结构蛋白。我们选择了 13 个 CD8+和 12 个 CD4+T 细胞表位,考虑了与 HLA Ⅰ类和 II 类分子结合的亲和力、基于与表位结合的不同 HLA 等位基因数量的混杂性以及免疫原性等参数。ZIKV 包膜蛋白结构域 III(EDIII)被添加到疫苗构建体中,形成了一种混合蛋白结构域-多表位疫苗。在 EDIII 中发现了三个高得分连续和两个不连续的 B 细胞表位。为了进一步提高候选疫苗的抗原性,我们测试了与四种不同蛋白佐剂偶联的疫苗的二级和三级结构和物理化学参数:鞭毛蛋白、50S 核糖体蛋白 L7/L12、肝素结合血凝素或 RS09 合成肽。添加鞭毛蛋白佐剂增加了疫苗的预测抗原性。计算机预测表明该蛋白是一种可能的抗原,无过敏原性,并且预测其稳定性。该疫苗的平均人群覆盖率估计为 87.86%,表明其可在全球范围内使用。对以前感染过 ZIKV 的个体的外周血单核细胞(PBMC)进行了测试,以检测针对所选 CD4 和 CD8 ZIKV 肽池产生细胞因子的情况。CD4+和 CD8+T 细胞在受到刺激后显著产生 IFN-γ,CD8+T 细胞也检测到 IL-2 的产生,这表明我们的肽有被特定 T 细胞识别并诱导免疫反应的潜力。总之,我们开发了一种基于计算机的通用疫苗,预测能诱导针对 ZIKV 的广泛且高覆盖率的细胞和体液免疫反应,这可能是后续体内验证的良好候选疫苗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53cb/8741764/fbf1c7841a16/41598_2021_3990_Fig1_HTML.jpg

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