Mechanistic Studies of Viral Host Cell Recognition and Entry and their Implication for Protein Design of Molecular Delivery Devices

摘要 在没有选择性给药的情况下，许多有希望的药物不会到达靶细胞，而是 会引起毒副作用。另一方面，许多病毒已经掌握了识别的艺术。 微环境线索，有选择地找到并感染特定的细胞。例如，它们依赖于“本地” 蛋白水解酶，有时是两种，以激活它们的融合蛋白。为了开发更好的目标设备，我们的目标是 剖析嵌入在病毒表面蛋白中的分子特性和功能，特别关注 受体相互作用、稳定性和融合触发(目标I)，我们将采用表面显示 以及传染性分析。我们将重点介绍副粘病毒(PMV)的病毒表面机制，特别是 副流感病毒5(PIV5)。大多数PMV都有保持宿主受体结合和细胞进入的分工 分离为两个独立的功能编码成两个分子：一个四聚体蛋白负责分子 识别和负责宿主和病毒膜合并的三聚体融合蛋白。这 间隔化使PMVS成为重新利用融合蛋白的极佳模型系统 保持不变，同时识别过程可以重新设计。 我们将利用深度突变扫描来评估所有可能的氨基酸 任何给定基因选择的替换。通过获取每个对象的不同适应度图 上述分子特性，我们将能够解决有关生物的有趣问题 病毒，例如在其蛋白质化学背景下的突变耐受性。重要的是，健身景观将 对交付设备的工程产生立竿见影的影响，因为它们将提供 这些复杂机械的分子结构。我们将使用所获得的序列-功能-结构图 用于开发一种新的、可适应的靶向递送平台，该平台将整合病毒表面 抗体碎片机械(AIM II)。关键的一点将是开发一种能够 整合抗体片段，同时保持病毒识别机制的所有调节功能 正常情况下，这涉及到构象变化的控制。以前的努力没有成功 开发高效、通用的交付系统。在这里，我们将获得并利用一个无价的数据库 病毒蛋白质结构和我们新获得的序列功能知识，我们将其与 新技术--蛋白质设计--来推进这个看似简单但雄心勃勃的工程项目。 我们的目标是为新的目标机制提供一个普遍适用的平台，该机制整合了这些 分子机制，同时也利用了大量识别和改造的抗体。 通过将部分病毒感染机制与抗体片段和适配蛋白相结合，我们 预计我们将能够显著推进药物和基因递送系统的开发，并 从而也为基因组工程提供了新的、急需的精确靶向技术。

Summary In the absence of selective delivery, many promising drugs do not reach the targeted cells, but rather cause toxic side effects. Many viruses, on the other hand, have mastered the art of identifying microenvironmental clues and selectively find and infect a specific cell. For instance, they depend on “local” proteases, sometimes two, to activate their fusion proteins. To develop better targeting devices, we aim to dissect molecular properties and functions embedded in viral surface proteins, specifically focusing on receptor interactions, stability, and fusion triggering (Aim I) for which we will employ surface display and infectivity assays. We will focus on the viral surface machinery of the paramyxoviruses (PMVs), specifically Parainfluenza virus 5 (PIV5). Most PMVs have a division of labor keeping host receptor binding and cell entry apart as two separate functions encoded into two molecules: one tetrameric protein responsible for molecular recognition and a trimeric fusion protein responsible for the merging of host and viral membranes. This compartmentalization makes the PMVs an excellent model system for repurposing as the fusion protein can remain untouched, while the recognition process can be re-engineered. We will take advantage of deep mutational scanning which allows us to evaluate all possible amino acid substitutions for any given genetic selection. By acquiring differential fitness landscapes for each of the aforementioned molecular properties, we will be able to address interesting questions about the biology of viruses, such as mutational tolerance in context of their protein chemistry. Importantly, fitness landscapes will have an immediate impact on engineering of delivery devices as they will provide rough blueprints of the molecular architecture of these complex machineries. We will use obtained sequence-function-structure maps for the development of a new, adaptable targeted delivery platform that will integrate viral surface machinery with antibody fragments (Aim II). The key point will be to develop an adapter molecule that integrates the antibody fragment while maintaining all regulatory function that the viral recognition machinery normally exhibits, which involves control of conformational changes. Previous efforts have not succeeded in developing an efficient, general delivery system. Here, we will obtain and leverage an invaluable database of virus protein structures together with our newly obtained sequence-function knowledge, which we combine with new technology – protein design – to advance this seemingly simple but ambitious engineering project. We aim to provide a generally applicable platform for a new targeting machinery that incorporates these molecular mechanisms while also taking advantage of the vast amount of identified and engineered antibodies. Through combining parts of the viral infection machinery with antibody fragments and adapter proteins, we anticipate that we will be able to significantly advance the development of drug and gene delivery systems and thereby also provide new and much needed precision targeting technology for genome engineering.