致病性病毒变体的不断进化和新病毒的出现加强了对广谱疫苗的需求以对抗此类威胁。可以有效地遏制导致流行和大流行感染的新病毒变体的传播,如果对新型病毒变体有效的广谱疫苗是容易获得的。广谱的发展,抗病毒的泛中和抗体,总的来说,在抗原性上非常不同——比如艾滋病毒,流感病毒和副粘病毒-已在文献中报道。通过使用计算机模拟方法分析了用于产生一系列批准的重组抗病毒疫苗的氨基酸序列,目的是鉴定可能适合开发基于广谱肽的抗病毒疫苗的高抗原性肽区域。这是通过使用开源数据来实现的,算法驱动的概率矩阵,并发布在计算机预测工具(SVMTriP,IEDB-AR,VaxiJen2.0,AllergenFPv.1.0,AllerTOPv.2.0,ToxinPred和ProtParam)评估抗原性,MHC-I和MHC-II结合潜力,免疫原性,变应原性,毒性和物理化学性质。我们报告了一个对MHC-I和MHC-II具有强亲和力的泛抗原肽区域,和良好的免疫原性潜力。根据相关仿真工具的输出,该肽被预测为无毒的,非过敏性和具有潜在的成功疫苗生产所需的物理化学性质。随着进一步的调查和优化,该肽可被考虑用于开发广谱抗病毒疫苗,该疫苗可预防新出现的新病毒。我们使用计算机模拟方法来鉴定具有所需物理化学性质的候选抗原肽的方法可能潜在地规避一些动物研究用于肽疫苗候选物评估的使用。
The constant evolution of pathogenic viral variants and the emergence of new viruses have reinforced the need for broad-spectrum vaccines to combat such threats. The spread of new viral variants leading to epidemic and pandemic infection can be effectively contained, if broad-spectrum vaccines effective against the newer viral variants are readily available. The development of broad-spectrum, pan-neutralising antibodies against viruses which, in general terms, are very antigenically different - such as HIV, influenza virus and paramyxoviruses - has been reported in the literature. The amino acid sequences used to generate a range of approved recombinant anti-viral vaccines were analysed by using in silico methods, with the aim of identifying highly antigenic peptide regions that may be suitable for the development of broad-spectrum peptide-based anti-viral vaccines. This was achieved through the use of open-source data, an algorithm-driven probability matrix, and published in silico prediction tools (SVMTriP, IEDB-AR, VaxiJen 2.0, AllergenFP v. 1.0, AllerTOP v. 2.0, ToxinPred and ProtParam) to evaluate antigenicity, MHC-I and MHC-II binding potential, immunogenicity, allergenicity, toxicity and physicochemical properties. We report a pan-antigenic peptide region with strong affinity for MHC-I and MHC-II, and good immunogenic potential. According to the output from the relevant in silico tools, the peptide was predicted to be non-toxic, non-allergic and to possess the desired physicochemical properties for potentially successful vaccine production. With further investigation and optimisation, this peptide could be considered for use in the development of a broad-spectrum anti-viral vaccine that may protect against emerging new viruses. Our approach of using in silico methods to identify candidate antigenic peptides with the desired physicochemical properties could potentially circumvent the use of some animal studies for peptide vaccine candidate evaluation.