Structural prediction of chimeric immunogens to elicit targeted antibodies against betacoronaviruses.

Jamel Simpson, Peter M Kasson
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Abstract

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. Experimental testing of five predicted-stable and two predicted-unstable chimeras confirmed 5/7 predictions, with one intermediate result. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.

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嵌合免疫原引发针对β冠状病毒的靶向抗体的结构预测。
Betacoronavirus构成了持续的流行病威胁。严重急性呼吸系统综合征冠状病毒2型病毒的抗原进化表明,大部分自发抗体反应都是狭隘的,而不是广泛中和,甚至可以对抗严重急性呼吸系冠状病毒2型变种,更不用说未来的威胁了。克服这一问题的一种方法是将抗体反应集中在病毒刺突蛋白的更好保守区域。在这里,我们提出了一种设计方法来预测严重急性呼吸系统综合征冠状病毒2型和其他冠状病毒之间的稳定嵌合体,创造出显示所需保守区域并改变其他区域的合成刺突蛋白。我们利用AlphaFold来预测嵌合结构,并基于AlphaFol德的输出创建了一个新的嵌合稳定性评分指标。我们使用这种方法评估了114个候选刺突嵌合体。使用分子动力学模拟作为中间验证技术对顶部嵌合体进行了进一步评估,与低评分对照相比显示出良好的稳定性。这证明了潜在方法的可行性,该方法可用于设计定制免疫原,以集中针对所需病毒糖蛋白表位的免疫反应。
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