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.

项目概要 由于每年的流行病及其大流行的潜力，流感病毒仍然是全球健康的负担。所以， 了解对这些病毒的免疫力并进一步研究开发改进的疫苗非常重要 高度重要性。流感血凝素（HA）和神经氨酸酶（NA）蛋白是流感病毒的主要靶标。 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 聚合酶以及人畜共患流感的 HA 和 NA 重配事件引起 病毒，这需要每年接种疫苗以防止流行的病毒株。然而，疫苗 由于流行毒株和疫苗毒株之间的不匹配，功效每年都有所不同。这种可变性 强调了开发改进的流感疫苗的重要性。我们和其他人最近发现 一类针对 H1N1 流感 HA 蛋白上保守的近膜表位的抗体， 称为锚定表位。该提案的总体目标是引发锚定的强大免疫反应 针对流感病毒的特异性且广泛中和的抗体。作为实现这一目标的主要工具，我们将 搭建锚定表位以测试支架将增加锚定表位的流行率的假设 特异性抗体单独或与可溶性重组 HA 一起作为初免-加强方案的一部分。在目标 1 中， 我们将利用计算策略来搭建锚定表位并使用以下方法快速筛选构建体 先前分离的抗锚抗体。支架将使用 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 候选蛋白将被重组表达并使用一组锚定靶向测试其抗原性 抗体以及热稳定性和单分散性。在目标 2 中，我们将确定 在小鼠疫苗接种和感染模型中锚定支架，以引发广泛中和 抗体。前三名候选者将接受免疫原性和引发锚定样能力的测试 小鼠中单独使用几种组合以及与流感 HA 蛋白的初免-加强方案中产生抗体。 然后，最优秀的候选者将在小鼠攻击模型中用两种不同的 H1N1 大流行病毒进行测试。 这个 R21 提案风险很高，因为我们将开发新的支架策略和候选疫苗，但它是 高回报，因为我们的方法有可能将菌株特异性抗体反应转向高度 保守且具有广泛保护性的表位。总的来说，我们的提案将开发脚手架的新方法 广泛中和蛋白表位，可应用于其他流感病毒和其他病毒糖蛋白 表位。