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用于预防人偏肺病毒(hMPV)的嵌合多表位疫苗的免疫信息学设计

Immunoinformatic design of chimeric multiepitope vaccine for the prevention of human metapneumovirus (hMPV).

作者信息

Ehsasatvatan Maryam, Kohnehrouz Bahram Baghban, Salavatizadeh Mohammad

机构信息

Department of Plant Breeding & Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, 51666, Iran.

Department of Pediatric Diseases, Faculty of Medicine, Urmia University of Medical Sciences, Urmia, Iran.

出版信息

BMC Infect Dis. 2025 Jul 30;25(1):964. doi: 10.1186/s12879-025-11339-x.


DOI:10.1186/s12879-025-11339-x
PMID:40739488
Abstract

BACKGROUND: Human metapneumovirus (hMPV) is a significant etiological agent of acute respiratory infections in children and immunocompromised individuals. Despite its growing clinical impact, no approved vaccines or targeted antiviral therapies are currently available. METHODS: An immunoinformatic approach was employed to design a chimeric multi-epitope vaccine candidate against hMPV. Conserved and virulence-associated proteins were analyzed to predict highly antigenic B cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes. The selected epitopes were screened for antigenicity, non-toxicity, non-allergenicity, and lack of homology to human proteins. The final construct included six B cell epitopes, six CTL epitopes, and two HTL epitopes, linked with appropriate adjuvants and Toll-like receptor (TLR) agonists. Structural modeling, molecular docking, and molecular dynamics simulations were conducted to evaluate the stability and receptor binding. Immunogenicity and expression potential were assessed through in silico immune simulation and codon optimization for expression in Escherichia coli. RESULTS: All selected epitopes showed high antigenicity with no allergenic or toxicity. Structural validation indicated a stable vaccine construct with favorable physicochemical properties. Molecular docking analysis predicted a high binding affinity between the vaccine construct and TLR2/TLR4 receptors. Molecular dynamics (MD) simulations suggested that the docked complexes maintained stable interactions under simulated physiological conditions. In silico immune simulations predicted strong B- and T-cell responses following three doses. Codon adaptation analysis supported the high-level expression in E. coli. CONCLUSION: The proposed multi-epitope vaccine demonstrates strong potential against hMPV, as supported by comprehensive computational analyses. Further experimental studies are required to validate its efficacy and safety.

摘要

背景:人偏肺病毒(hMPV)是儿童和免疫功能低下个体急性呼吸道感染的重要病原体。尽管其临床影响日益增大,但目前尚无获批的疫苗或靶向抗病毒疗法。 方法:采用免疫信息学方法设计一种针对hMPV的嵌合多表位疫苗候选物。分析保守蛋白和与毒力相关的蛋白,以预测高抗原性的B细胞、细胞毒性T淋巴细胞(CTL)和辅助性T淋巴细胞(HTL)表位。对所选表位进行抗原性、无毒性、无致敏性以及与人蛋白无同源性的筛选。最终构建体包含六个B细胞表位、六个CTL表位和两个HTL表位,与合适的佐剂和Toll样受体(TLR)激动剂相连。进行结构建模、分子对接和分子动力学模拟以评估稳定性和受体结合情况。通过计算机免疫模拟和密码子优化评估在大肠杆菌中表达的免疫原性和表达潜力,以实现在大肠杆菌中的表达。 结果:所有所选表位均显示出高抗原性,无致敏性或毒性。结构验证表明疫苗构建体稳定,具有良好的理化性质。分子对接分析预测疫苗构建体与TLR2/TLR4受体之间具有高结合亲和力。分子动力学(MD)模拟表明对接复合物在模拟生理条件下保持稳定的相互作用。计算机免疫模拟预测三剂接种后会产生强烈的B细胞和T细胞反应。密码子适应性分析支持在大肠杆菌中的高水平表达。 结论:综合计算分析表明,所提出的多表位疫苗对hMPV具有强大的潜力。需要进一步的实验研究来验证其有效性和安全性。

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引用本文的文献

[1]
Correction: Immunoinformatic design of chimeric multiepitope vaccine for the prevention of human metapneumovirus (hMPV).

BMC Infect Dis. 2025-9-2

本文引用的文献

[1]
The global burden of human metapneumovirus-associated acute respiratory infections in older adults: a systematic review and meta-analysis.

Lancet Healthy Longev. 2025-2

[2]
Designing and immunomolecular analysis of a new broad-spectrum multiepitope vaccine against divergent human papillomavirus types.

PLoS One. 2024-12-2

[3]
Designing multi-epitope vaccine against human cytomegalovirus integrating pan-genome and reverse vaccinology pipelines.

Biologicals. 2024-8

[4]
Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1.

3 Biotech. 2024-7

[5]
Accurate structure prediction of biomolecular interactions with AlphaFold 3.

Nature. 2024-6

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Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer.

Sci Rep. 2024-5-4

[7]
DeepLoc 2.1: multi-label membrane protein type prediction using protein language models.

Nucleic Acids Res. 2024-7-5

[8]
Development of a novel multi-epitope mRNA vaccine candidate to combat HMPV virus.

Hum Vaccin Immunother. 2023-12-15

[9]
BepiPred-3.0: Improved B-cell epitope prediction using protein language models.

Protein Sci. 2022-12

[10]
Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus.

Viruses. 2022-10-27

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