疫苗已经大大减少了许多致命的病毒感染的影响。然而,鉴于反复发生的大流行和流行病,越来越需要加快疫苗的开发。此外,由于各种因素,识别针对某些病毒的疫苗具有挑战性,特别是不能在细胞培养物中培养某些病毒,以及人类MHC谱的广泛多样性。幸运的是,反向疫苗(RV)有效地克服了这些限制,并简化了整个蛋白质组抗原蛋白表位的鉴定,简化疫苗开发过程。此外,它使得能够产生多表位疫苗,所述多表位疫苗能够有效地解释人类群体中MHC谱的变化。RV方法在开发针对病毒病原体的精确和有效的疫苗方面提供了许多优势,包括广泛的蛋白质组覆盖,准确的表位鉴定,交叉保护能力,MHC相容性。随着RV的推出,研究人员越来越重视创建基于多表位的疫苗,旨在刺激宿主对多种血清型的免疫反应,与单组分单价替代品相反。不管基于RV的候选疫苗看起来多么有前途,它们必须经过实验验证,以探索其在实际应用中的保护功效。时间,努力,现在可以将分配给费力的表位鉴定过程的资源重定向到通过RV方法鉴定的验证疫苗候选物。然而,为了克服基于RV的方法中的失败,必须努力纳入免疫学原理,并考虑靶向涉及疾病发病机理的表位区域,免疫反应,和中和抗体成熟。在RV中整合多组学并整合人工智能和基于机器学习的工具和技术将增加开发有效疫苗的机会。这篇评论彻底解释了RV方法,理想的基于RV的疫苗构建组件,基于RV的疫苗旨在对抗病毒病原体,其挑战,和未来的前景。
Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain viruses is challenging due to various factors, notably the inability to culture certain viruses in cell cultures and the wide-ranging diversity of MHC profiles in humans. Fortunately, reverse vaccinology (RV) efficiently overcomes these limitations and has simplified the identification of epitopes from antigenic proteins across the entire proteome, streamlining the vaccine development process. Furthermore, it enables the creation of multiepitope vaccines that can effectively account for the variations in MHC profiles within the human population. The RV approach offers numerous advantages in developing precise and effective vaccines against viral pathogens, including extensive proteome coverage, accurate epitope identification, cross-protection capabilities, and MHC compatibility. With the introduction of RV, there is a growing emphasis among researchers on creating multiepitope-based vaccines aiming to stimulate the host\'s immune responses against multiple serotypes, as opposed to single-component monovalent alternatives. Regardless of how promising the RV-based vaccine candidates may appear, they must undergo experimental validation to probe their protection efficacy for real-world applications. The time, effort, and resources allocated to the laborious epitope identification process can now be redirected toward validating vaccine candidates identified through the RV approach. However, to overcome failures in the RV-based approach, efforts must be made to incorporate immunological principles and consider targeting the epitope regions involved in disease pathogenesis, immune responses, and neutralizing antibody maturation. Integrating multi-omics and incorporating artificial intelligence and machine learning-based tools and techniques in RV would increase the chances of developing an effective vaccine. This review thoroughly explains the RV approach, ideal RV-based vaccine construct components, RV-based vaccines designed to combat viral pathogens, its challenges, and future perspectives.