Immunoinformatics method to design universal multi-epitope nanoparticle vaccine for TGEV S protein

表位 病毒学 计算生物学 生物 抗体 免疫学
作者
Shinian Li,Jingjing Yu,Chencheng Xiao,Yaling Li
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:15 (1) 被引量:2
标识
DOI:10.1038/s41598-025-95602-w
摘要

Porcine transmissible enteritis virus (TGEV) is a fatal pathogen affecting newborn piglets, presenting a significant challenge to global intensive pig farming biosecurity due to its ongoing mutation. There is still a lack of effective vaccines to combat this virus, Vaccination has long been considered the most effective way to overcome infectious diseases, however, traditional vaccines cannot be brought to market quickly enough to deal with rapid mutations and emerging viruses. Therefore, this study addresses this gap by using immunoinformatics methods and ferritin nanoparticle delivery system to build a platform for rapid research and development of porcine coronavirus vaccine, designing a candidate nanoparticle vaccine that targets the TGEV S protein. To this end, multiple servers and strict screening criteria were used to analyze the S protein, and 3 CTL dominant epitopes, 3 Th dominant epitopes, and 6 B cell dominant epitopes were obtained. The candidate nanoparticle vaccine was constructed by incorporating ferritin sequences through the C-terminus after they were tandemly linked in a certain order using a flexible linker. Further experimental analyses showed that the designed candidate nanoparticle vaccine possessed relatively high antigenicity, immunogenicity, non-allergenicity, non-transmembrane proteins, suitable physicochemical properties, and high solubility upon overexpression. Tertiary structure modeling and disulfide engineering ensured conformational similarity to natural proteins and high stability. Additionally, the model predicted 6 Linear Epitopes and 6 Discontinuous Epitopes for B-cell conformational epitopes. Docking with TLR-3 and TLR-4 molecules shows a large number of interacting hydrogen-bonded amino acid residues and hydrophobically interacting amino acid residues. Immunomimetic assays show high levels of immunoglobulin, T-lymphocyte and IFN-γ secretion and may elicit specific immune responses. Through computerized cloning, the candidate nanoparticle vaccine can be efficiently expressed in the E. coli K12 expression system, aligning with future large-scale industrial production strategies. Overall, the results indicate that the constructed candidate nanoparticle vaccine can be effectively expressed and may be able to induce a strong immune response, which is expected to be an ideal candidate vaccine against TGEV.
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