Zhang Jingjing, Yang Youfang, Wang Binyu, Qiu Wanting, Zhang Helin, Qiu Yuyang, Yuan Jing, Dong Rong, Zha Yan
School of Basic Medicine, Guangzhou Medical University, Guangzhou, China.
Department of Nephrology, Guizhou Provincial People's Hospital, Guiyang, China.
Front Immunol. 2024 Dec 5;15:1427677. doi: 10.3389/fimmu.2024.1427677. eCollection 2024.
Borna disease virus 1 (BoDV-1) is an emerging zoonotic RNA virus that can cause severe acute encephalitis with high mortality. Currently, there are no effective countermeasures, and the potential risk of a future outbreak requires urgent attention. To address this challenge, the complete genome sequence of BoDV-1 was utilized, and immunoinformatics was applied to identify antigenic peptides suitable for vaccine development.
Immunoinformatics and antigenicity-focused protein screening were employed to predict B-cell linear epitopes, B-cell conformational epitopes, and cytotoxic T lymphocyte (CTL) epitopes. Only overlapping epitopes with antigenicity greater than 1 and non-toxic, non-allergenic properties were selected for subsequent vaccine construction. The epitopes were linked using GPGPG linkers, incorporating β-defensins at the N-terminus to enhance immune response, and incorporating Hit-6 at the C-terminus to improve protein solubility and aid in protein purification. Computational tools were used to predict the immunogenicity, physicochemical properties, and structural stability of the vaccine. Molecular docking was performed to predict the stability and dynamics of the vaccine in complex with Toll-like receptor 4 (TLR-4) and major histocompatibility complex I (MHC I) receptors. The vaccine construct was cloned through in silico restriction to create a plasmid for expression in a suitable host.
Among the six BoDV-1 proteins analyzed, five exhibited high antigenicity scores. From these, eight non-toxic, non-allergenic overlapping epitopes with antigenicity scores greater than 1 were selected for vaccine development. Computational predictions indicated favorable immunogenicity, physicochemical properties, and structural stability. Molecular docking analysis showed that the vaccine remained stable in complex with TLR-4 and MHC I receptors, suggesting strong potential for immune recognition. A plasmid construct was successfully generated, providing a foundation for the experimental validation of vaccines in future pandemic scenarios.
These findings demonstrate the potential of the immunoinformatics-designed multi-epitope vaccines for the prevention and treatment of BoDV-1. Relevant preparations were made in advance for possible future outbreaks and could be quickly utilized for experimental verification.
博尔纳病病毒1型(BoDV-1)是一种新出现的人畜共患RNA病毒,可引发严重的急性脑炎,死亡率很高。目前,尚无有效的应对措施,未来爆发的潜在风险需要紧急关注。为应对这一挑战,利用了BoDV-1的完整基因组序列,并应用免疫信息学来鉴定适合疫苗开发的抗原肽。
采用免疫信息学和以抗原性为重点的蛋白质筛选来预测B细胞线性表位、B细胞构象表位和细胞毒性T淋巴细胞(CTL)表位。仅选择抗原性大于1且具有无毒、无过敏特性的重叠表位用于后续疫苗构建。使用GPGPG接头连接表位,在N端掺入β-防御素来增强免疫反应,在C端掺入Hit-6以提高蛋白质溶解度并有助于蛋白质纯化。使用计算工具预测疫苗的免疫原性、理化性质和结构稳定性。进行分子对接以预测疫苗与Toll样受体4(TLR-4)和主要组织相容性复合体I(MHC I)受体复合物的稳定性和动力学。通过计算机限制性克隆疫苗构建体,以创建用于在合适宿主中表达的质粒。
在所分析的六种BoDV-1蛋白中,有五种表现出高抗原性评分。从中选择了八个抗原性评分大于1的无毒、无过敏重叠表位用于疫苗开发。计算预测表明其具有良好的免疫原性、理化性质和结构稳定性。分子对接分析表明,该疫苗与TLR-4和MHC I受体复合物保持稳定,表明具有很强的免疫识别潜力。成功生成了质粒构建体,为未来大流行情况下疫苗的实验验证奠定了基础。
这些发现证明了免疫信息学设计的多表位疫苗在预防和治疗BoDV-1方面的潜力。提前为未来可能的爆发做好了相关准备,并且可以迅速用于实验验证。