Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS Comput Biol. 2022 Sep 26;18(9):e1010563. doi: 10.1371/journal.pcbi.1010563. eCollection 2022 Sep.
The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2' cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.
SARS-CoV-2 变种的出现以及人畜共患冠状病毒引发的疫情历史表明，需要开发新一代疫苗，以提供针对变种毒株的保护。在这里，我们结合了冠状病毒刺突的不同序列和结构分析，以及深度突变扫描的数据，设计了包含可能出现的最重要突变的 SARS-CoV-2 变种抗原。我们训练了一个神经网络来预测 RBD 表达和 ACE2 结合的序列，这使我们能够确定这些抗原是稳定的并且与 ACE2 结合。因此，它们代表了可行的变体。然后，我们使用亲和力成熟 (AM) 的计算模型来研究用不同组合的设计抗原进行免疫接种的抗体反应。结果表明，与单独用野生型病毒免疫接种或感染相比，用抗原混合物免疫接种可能会促进针对 SARS-CoV-2 变体的抗体滴度的更高进化。最后，我们对来自不同属的 12 种冠状病毒的分析确定了 S2' 切割位点和融合肽作为潜在的泛冠状病毒疫苗靶点。
