Table_2_AI Aided Design of Epitope-Based Vaccine for the Induction of Cellular Immune Responses Against SARS-CoV-2.csv

The heavy burden imposed by the COVID-19 pandemic on our society triggered the race toward the development of therapies or preventive strategies. Among these, antibodies and vaccines are particularly attractive because of their high specificity, low probability of drug-drug interaction, and potentially long-standing protective effects. While the threat at hand justifies the pace of research, the implementation of therapeutic strategies cannot be exempted from safety considerations. There are several potential adverse events reported after the vaccination or antibody therapy, but two are of utmost importance: antibody-dependent enhancement (ADE) and cytokine storm syndrome (CSS). On the other hand, the depletion or exhaustion of T-cells has been reported to be associated with worse prognosis in COVID-19 patients. This observation suggests a potential role of vaccines eliciting cellular immunity, which might simultaneously limit the risk of ADE and CSS. Such risk was proposed to be associated with FcR-induced activation of proinflammatory macrophages (M1) by Fu et al. (2020) and Iwasaki and Yang (2020). All aspects of the newly developed vaccine (including the route of administration, delivery system, and adjuvant selection) may affect its effectiveness and safety. In this work we use a novel in silico approach (based on AI and bioinformatics methods) developed to support the design of epitope-based vaccines. We evaluated the capabilities of our method for predicting the immunogenicity of epitopes. Next, the results of our approach were compared with other vaccine-design strategies reported in the literature. The risk of immuno-toxicity was also assessed. The analysis of epitope conservation among other Coronaviridae was carried out in order to facilitate the selection of peptides shared across different SARS-CoV-2 strains and which might be conserved in emerging zootic coronavirus strains. Finally, the potential applicability of the selected epitopes for the development of a vaccine eliciting cellular immunity for COVID-19 was discussed, highlighting the benefits and challenges of such an approach.

新型冠状病毒肺炎（COVID-19）大流行给全球社会带来了沉重负担，催生了治疗手段与预防策略的研发竞赛。其中，抗体与疫苗凭借高特异性、低药物相互作用风险，以及潜在的长效保护作用，成为极具吸引力的研发方向。尽管当前的疫情形势推动了研发节奏，但治疗策略的实施仍需严格遵循安全性考量。目前已有多项针对疫苗接种或抗体治疗后潜在不良事件的报道，其中两项最为关键：抗体依赖增强效应（antibody-dependent enhancement, ADE）与细胞因子风暴综合征（cytokine storm syndrome, CSS）。另一方面，有研究显示新型冠状病毒肺炎患者体内T细胞（T-cells）的耗竭与功能衰竭与不良预后密切相关。这一发现提示，诱导细胞免疫的疫苗或许能发挥潜在作用，同时降低ADE与CSS的发生风险。Fu等人（2020）以及Iwasaki与Yang（2020）曾提出，该风险与Fc受体（FcR）介导的促炎巨噬细胞（M1型）激活存在关联。新型疫苗的所有研发环节（包括接种途径、递送系统与佐剂选择）均可能影响其有效性与安全性。本研究采用一种基于人工智能（AI）与生物信息学方法开发的新型计算机模拟方法（in silico approach），用于辅助基于表位的疫苗（epitope-based vaccines）设计。我们评估了该方法预测表位免疫原性的能力。随后，将本方法的预测结果与文献中报道的其他疫苗设计策略进行了对比。同时还评估了免疫毒性风险。为便于筛选可在不同严重急性呼吸综合征冠状病毒2（SARS-CoV-2）毒株间共享，且可能在新型动物源性冠状病毒（zootic coronavirus）毒株中保守存在的肽段，本研究对冠状病毒科（Coronaviridae）内其他病毒的表位保守性进行了分析。最后，本研究探讨了所筛选表位用于开发新型冠状病毒肺炎细胞免疫疫苗的潜在适用性，并着重分析了该策略的优势与挑战。