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利用免疫信息学方法设计针对人鼻病毒C的多表位疫苗候选物。

Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach.

作者信息

Mamun Tajul Islam, Ali Md Ahad, Hosen Md Nazmul, Rahman Jillur, Islam Md Anwarul, Akib Md Golam, Zaman Kamruz, Rahman Md Masudur, Hossain Ferdaus Mohd Altaf, Ibenmoussa Samir, Bourhia Mohammed, Dawoud Turki M

机构信息

Department of Epidemiology and Public Health, Sylhet Agricultural University, Sylhet, Bangladesh.

Faculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.

出版信息

Front Immunol. 2025 Jan 7;15:1364129. doi: 10.3389/fimmu.2024.1364129. eCollection 2024.

Abstract

Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in , with a Codon Adaptation Index of 0.99 and GC content of 54.58%. The minimum free energy of the RNA secondary structure was -494.90 kcal/mol. While our findings suggest the potential effectiveness of the designed vaccine candidate against HRV-C, further and investigations are warranted to validate its safety and efficacy.

摘要

人鼻病毒C(HRV-C)是儿童呼吸道感染的重要病原体,并且与各年龄组的哮喘加重有关。尽管其有影响,但目前尚无针对HRV-C的许可疫苗。在此,我们提出一种新方法来填补这一空白,即采用免疫信息学技术设计一种基于多表位的抗HRV-C疫苗。从NCBI服务器以FASTA格式下载所选结构蛋白VP1和VP2以及HRV-C非结构蛋白2C的序列,以进行进一步分析。通过对HRV-C基因组序列的详尽分析,我们鉴定出能够引发保护性免疫反应的高度保守的免疫原性区域。利用先进的免疫信息学工具,我们预测了B细胞、细胞毒性T淋巴细胞和辅助性T淋巴细胞的表位,确保对不同HRV-C毒株有广泛覆盖。通过将选定抗原与免疫原性表位和佐剂整合,并使用最佳接头,构建了候选疫苗。开发了三种疫苗构建体,其中V2最具前景,由480个氨基酸残基组成。V2表现出强抗原性、无致敏性和溶解性,溶解度得分大于0.550,并表现出优异的结构稳定性,在拉氏图最有利区域中有91.9%的残基。分子动力学和模拟研究揭示了稳定的疫苗-TLR8复合物,结合能为-296.15,均方根偏差值一致。此外,电子克隆和序列优化确保了在 中的高效表达,密码子适应指数为0.99,GC含量为54.58%。RNA二级结构的最小自由能为-494.90千卡/摩尔。虽然我们的研究结果表明设计的候选疫苗对HRV-C可能有效,但仍需要进一步的 和 研究来验证其安全性和有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58a2/11747413/61a730c49988/fimmu-15-1364129-g001.jpg

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