Computationally designed anchor scaffolds for elicitation of broadly neutralizing influenza antibodies

计算设计的锚支架，用于引发广泛中和流感抗体

• 批准号: 10727168
• 负责人: Jarrod Mousa
• 金额: $ 4.04万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-22 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10727168
• 关键词: Animal Model; Antibodies; Antibody Response; B-Lymphocytes; Binding; Classification; DNA-Directed RNA Polymerase; Development; Epidemic; Epitopes; Event; Experimental Designs; Glycoproteins; Goals; Head; Hemagglutinin; Immune; Immune response; Immunity; Immunology; Infection; Influenza; Influenza A Virus, H1N1 Subtype; Influenza Hemagglutinin; Machine Learning; Membrane; Modeling; Mus; Mutation; Network-based; Neuraminidase; Prevalence; Property; Protein Engineering; Proteins; Rapid screening; Recombinants; Regimen; Research; Research Personnel; Site; Surface; Technology; Testing; Vaccinated; Vaccination; Vaccines; Viral; Virus; Work; Zoonoses; anti-influenza; cross reactivity; design; efficacy evaluation; global health; high reward; high risk; human subject; immunogenicity; improved; influenza infection; influenza virus vaccine; influenzavirus; innovation; machine learning method; monomer; mouse model; neural network; neutralizing antibody; novel; novel strategies; pandemic potential; pandemic virus; pathogen; response; scaffold; stem; tool; vaccine candidate; vaccine efficacy

Project Summary Influenza viruses remain a global health burden due to yearly epidemics and their pandemic potential. Therefore, understanding immunity to these viruses and further research on the development of improved vaccines is of high importance. The influenza hemagglutinin (HA) and neuraminidase (NA) proteins are the major targets of protective antibodies. Long-term protection to influenza viruses remains a challenge due to high mutation rates caused by a low-fidelity RNA polymerase as well as reassortment events of HA and NA with zoonotic influenza viruses, and this necessitates annual vaccination for protection against circulating strains. However, vaccine efficacy varies year to year due to mismatches between circulating strains and vaccine strains. This variability highlights the importance of developing improved influenza vaccines. We and others have recently discovered a class of antibodies targeting a conserved membrane-proximal epitope on the H1N1 influenza HA protein, termed the anchor epitope. The overall goal of this proposal is to elicit a robust immune response of anchor- specific and broadly neutralizing antibodies to influenza virus. As a main tool to achieve this goal, we will be scaffolding the anchor epitope to test the hypothesis that the scaffold will increase the prevalence of anchor- specific antibodies alone or together with a soluble recombinant HA as part of a prime-boost regimen. In Aim 1, we will utilize a computational strategy to scaffold the anchor epitope and rapidly screen constructs using previously isolated anti-anchor antibodies. Scaffolds will be generated using a combination of Rosetta and machine learning-based approaches to design and predict the stability and folding of the novel proteins. The top candidate proteins will be recombinantly expressed and tested for antigenicity using a panel of anchor-targeting antibodies as well as for thermal stability and monodispersion. In Aim 2, we will determine the efficacy of the anchor scaffolds in the mouse vaccination and infection models for the elicitation of broadly neutralizing antibodies. The top three candidates will be tested for immunogenicity and the ability to elicit anchor-like antibodies in mice using several combinations alone and in a prime-boost regimen with influenza HA protein. The top candidate will then be tested in a mouse challenge model with two different H1N1 pandemic viruses. This R21 proposal is high risk as we will develop new scaffolding strategies and vaccine candidates, but it is high reward as our approach has the potential to redirect strain-specific antibody responses toward a highly conserved, and broadly protective epitope. Overall, our proposal will develop new approaches for scaffolding broadly neutralizing protein epitopes, which could be applied to additional influenza and other viral glycoprotein epitopes.

项目摘要 由于年度流行病及其大流行潜力，流感病毒仍然是全球健康负担。所以， 了解对这些病毒的免疫力，并进一步研究改善疫苗的开发是 非常重要。流感血凝素（HA）和神经氨酸酶（Na）蛋白是主要靶标 保护性抗体。由于高突变率，对流感病毒的长期保护仍然是一个挑战 由低保真RNA聚合酶以及HA和NA的重新分类事件引起的HA和NA与人畜共患流感 病毒，这需要每年的疫苗接种以防止循环菌株。但是，疫苗 由于循环菌株和疫苗菌株之间的不匹配，疗效每年都会变化。这种变异性 强调了发展改善流感疫苗的重要性。我们和其他人最近发现 一类针对H1N1流感蛋白上的保守膜透明表位的抗体， 称为锚点表位。该提议的总体目标是引起锚定的强大免疫反应 - 特异性且广泛中和对流感病毒的抗体。作为实现这一目标的主要工具，我们将 脚手架锚点表位以检验脚手架会增加锚固率的假设 特定的抗体单独或与可溶性重组HA一起作为黄金促进方案的一部分。在AIM 1中， 我们将利用计算策略来使用锚点表位和快速筛选结构 以前孤立的抗锚抗体。脚手架将使用Rosetta和 基于机器学习的方法来设计和预测新型蛋白质的稳定性和折叠。顶部 候选蛋白将通过锚定靶向进行重组表达并测试抗原性 抗体以及热稳定性和单分散性。在AIM 2中，我们将确定 小鼠疫苗接种和感染模型中的锚脚支架，以广泛中和 抗体。前三名候选人将测试免疫原性和引起类似锚的能力 单独使用几种组合和带有流感HA蛋白的原始促进疗法中的小鼠抗体。 然后，将在具有两个不同H1N1大流行病毒的小鼠挑战模型中对顶级候选者进行测试。 R21提案是高风险，因为我们将制定新的脚手架策略和候选疫苗，但这是 高奖励，因为我们的方法有可能重定向菌株特异性抗体反应 保守和广泛保护的表位。总体而言，我们的建议将开发脚手架的新方法 广泛中和蛋白质表位，可以应用于其他流感和其他病毒糖蛋白 表位。