Optimization of a computationally designed antiviral for influenza

 描述（由申请人提供）：流感是美国死亡和发病的主要原因，每年导致多达40，000人死亡，约200，000人住院治疗和> 104亿美元的费用。目前的抗病毒药物耐药率高，疗效低，因此迫切需要开发更好的方法来预防季节性流感和未来的大流行。我们的目标是开发计算设计的肽作为暴露前预防和暴露后治疗流感。我们已经证明，一个小的计算设计的蛋白质（HB36.6），干扰流感感染的高度保守的血凝素干细胞区结合和中和广泛的流感病毒变种，包括大流行株和耐药株目前的抗病毒药物。当鼻内递送时，这种流感结合剂赋予小鼠针对不同流感毒株的完全预防性和治疗性保护，这一结果首次证明了通过这种计算方法设计的理论靶标转化为具有强体内生物效力的新的抗病毒药物。在该应用中，我们提出以我们对HB 36.6的有希望的发现为基础，并通过计算设计将有效对抗流感的从头超稳定微型蛋白结合剂（30-40个氨基酸）来扩大功效，提供泛特异性免疫应答。 保护免受更广泛的流感病毒株。这些新的超稳定迷你粘合剂将更小，更稳定，具有更高的生物利用度，并且比我们目前的领先1组粘合剂HB 36.6具有更低的制造成本。我们假设，优化的计算设计的微型蛋白结合剂将提供优越的上级广泛的，有效的预防和治疗保护小鼠对组1病毒。我们将确定计算设计的微型蛋白的表达和体外中和，并确定一个单一的微型蛋白结合剂，提供最好的预防和治疗保护与致死剂量的组1流感病毒的小鼠。如果成功，这些实验将建立一类新的抗流感病毒药物，可以克服目前市场上抗流感病毒药物的局限性，并为未来的开发建立一个强大的临床前数据包。

 DESCRIPTION (provided by applicant): Influenza is a leading cause of death and morbidity in the US, resulting in up to 40,000 deaths, ~200,000 hospitalizations and > $10.4 billion in expenses per year. Current antivirals incur high resistance rates and have low efficacy so there is a crucial need to develop better approaches to protect from seasonal influenza and future pandemics. We aim to develop computationally designed peptides as a pre-exposure prophylactic and post-exposure therapeutic against influenza. We have shown that a small computationally designed protein (HB36.6), interferes with influenza infection by binding the highly conserved hemagglutinin stem region and neutralizes a wide range of influenza variants including pandemic strains and strains resistant to current antivirals. When delivered intranasally, this influenza binder confers complete prophylactic and therapeutic protection against different influenza strains in mice, a result that demonstrates for the first time, transformation of a theoretical target designed by this computational method into a new antiviral with strong biopotency in vivo. In this application, we propose to build on our promising findings with HB36.6 and broaden efficacy by computationally designing de novo hyperstable mini-protein binders (30-40 amino acids) that will be effective against influenza providing pan-specific protection against a broader range of influenza strains. These new hyperstable mini-binders, will be smaller, more stable, have increased bioavailability, and will have a lower cost of manufacturing than our current lead Group 1 binder HB36.6. We hypothesize that the optimized computationally designed mini-protein binders will afford superior broad, potent prophylactic and therapeutic protection in mice against Group 1 viruses. We will determine expression and in vitro neutralization of computationally designed mini-proteins and identify a single mini-protein binder that affords the best prophylactic and therapeutic protection in mice challenged with a lethal dose of Group 1 influenza virus. If successful, these experiments will establish a new class of flu antivirals that could overcome the limitations of currently marketed flu antivirals an build a strong preclinical data package for future development.