Hybrid Methods for Prediction and Design of Novel Human Influenza Antibodies

现提出的“新型人流感抗体的杂交预测与设计方法” 将识别和开发新的流感抗体。已知的流感病毒有三种， 其中A型流感根据血凝素(HA)进一步分为2组，17个亚型。 甲型H1型和H3型流感病毒季节性感染人类。抗体的几种高分辨结构 用X射线结晶学测定了甲型流感血凝素的含量。与病毒相互作用的抗体 抗原性不同的三聚体HA分子的头部区域通常宽度较窄。最近，有两个 已经描述了多种类型的抗体，它们表现出广泛的中和能力，包括多种亚型的流感。这些 两种类型的抗体结合更保守的HA干区或保守的唾液酸受体结合 头部区域内的口袋。 H5N1流感病毒传统上是感染禽类的，但最近爆发了几起疫情 仅限于鸟类传人。最近的研究描述了H5N1流感的适应情况 从雪貂到雪貂的呼吸道飞沫传播率，这可能模拟了未来高度 自然界中人类H5病毒的致病性大流行。人们对人类如何接种常规疫苗知之甚少 H5免疫原可能被这种突变体保护，使其免受感染或疾病，这些突变体具有有限的 HA中表面点突变的数量。我们提供了分离人类中和细胞的初步数据。 识别野生型和呼吸道传播飞沫的H5头区的单抗 H5来自接种了常规H5 HA蛋白疫苗的人。这样做的第一个目标是 建议建立一条“快速”管道，快速识别和鉴定人类抗体， 广泛中和流感病毒--快速应对新出现威胁的重要战略 为人类健康干杯。 我们最近证明了一种名为“多态设计”的新计算方法可以概括。 抗体在电子计算机中成熟，即预测突变，增加抗体与其目标的亲和力，还 预测编码能够广泛识别多靶点的抗体蛋白的抗体序列 蛋白质。这项建议的第二个目标是设计和测试(A)在硅胶成熟期的快速 头部结合抗体以增加对HA抗原的亲和力和(B)多状态设计以创建 识别多种不同分支、群或甚至类型的HAS的茎结合抗体。

The present proposal “Hybrid Methods for Prediction and Design of Novel Human Influenza Antibodies” will identify and develop novel influenza antibodies. There are three types of influenza viruses known, of which influenza type A is further differentiated into 2 groups, 17 subtypes based on the hemagglutinin (HA). Influenza A subtype H1 and H3 viruses seasonally infect humans. Several high-resolution structures of antibodies engaging influenza A HA have been determined by X-ray crystallography. Antibodies that engage the antigenically diverse head region of the trimeric HA molecules are most often narrow in breadth. Recently, two types of antibodies have been described that exhibit broad neutralization multiple subtypes of influenza. These two types of antibodies bind the more conserved stem region of HA or the conserved sialic acid receptor binding pocket within the head region. H5N1 influenza viruses traditionally infect birds, but have been responsible for several recent outbreaks limited to bird-to-human transmission. Recent research described adaptations of influenza H5N1 that confer respiratory droplet transmissibility from ferret to ferret, which may mimic the future development of a highly pathogenic pandemic human H5 virus in nature. It is poorly understood how humans vaccinated with conventional H5 immunogens might be protected from infection or disease with such mutants, which possess a limited number of surface point mutations in the HA. We present preliminary data on the isolation of human neutralizing monoclonal antibodies to the H5 head domain that recognize both wild-type and respiratory droplet transmissible H5 HAs from humans vaccinated with conventional H5 HA protein vaccine. The first objective of this proposal is to establish a pipeline ‘RAPID’ to rapidly identify and characterize human antibodies that broadly neutralize influenza viruses – an important strategy for the swift response to emerging threats to human health. We recently demonstrated that a new computational method termed “multi-state design” can recapitulate antibody maturation in silico, i.e., predicts mutations that increase antibody affinity to its target, and also predict antibody sequences encoding antibody proteins that are capable of broadly recognizing multiple target proteins. The second objective of this proposal is to design and test RAPID for (a) in silico maturation of head-binding antibodies to increase affinity for the HA antigen and (b) multi-state design to create stem-binding antibodies that recognize HAs of multiple different clades, groups, or even types.