Multivalent protein-DNA nanostructures as synthetic blocking antibodies

项目摘要 蛋白质-蛋白质相互作用(PPI)驱动着生物学中无数的过程。阻止这些互动的能力 高特异性是探索这些过程的基础科学以及发展成像的关键 代理或新的治疗方法。然而，大多数传统的用于阻止蛋白质相互作用的分子-如 小分子、多肽或抗体-依赖于关键界面或结合口袋的精确靶向， 对于一些目标来说，这可能是困难的。此外，这些方法都不能很容易地调整为与 靶标的价态或大小，以及与未直接参与PPI的蛋白质上的斑块结合可能无法阻止 活动。在这里，我们建议开发一种纳米级的合成抗体(“纳米合成体”)，它由一个可调节的 含有2-3个多肽/蛋白质配体的DNA纳米结构，可以结合到目标蛋白质的不同表面和 通过DNA结构的立体结构阻止其与伴侣的联系。个体多肽/蛋白质 结合剂将从已知分子中衍生，或通过噬菌体等方法独立找到 展示。关键的是，我们的方法融合了计算模拟--并在电子计算机上“进化”--这些混合体 蛋白质-DNA纳米合成体，创建一个结构库，并探测它们与靶标的关联。我们 目的是建立一个反馈循环，由此计算模拟产生候选纳米合成体，可以 进行实验测试，为下一轮模拟提供进一步的信息。我们将首先将此管道应用于 抗SARS-CoV-2刺突蛋白三聚体的高三聚体纳米合成体(目标1)。这张试验台将允许我们 优化工艺，找到高亲和力的封闭结构。然后，我们将把我们的方法应用于纳米合成体 用于阻止纤维蛋白原组装成纤维蛋白凝块(目标2)。第二个目标将涉及抗噬菌体展示 纤维蛋白寻找新的结合剂，从而将它们转化为高亲和力的杂三价结构。在这两个地方 目的，我们将展示纳米结构配体呈现相对于简单齐聚的优势 带有柔性链接器。总而言之，我们的工作将产生一种新的计算-实验范式 设计可调节的、用户定义的纳米结构，可以呈现三个或更多用于结合的多肽/蛋白质 任何蛋白质，并阻止其与其目标的联系。重要的是，我们的方法不需要直接绑定 到界面，这应该使它能够靶向更大范围的蛋白质，这些蛋白质可能不符合 传统的方法，大的蛋白质复合体，或可能逃脱单一目标的突变/变种 粘合剂。

Project Summary Protein-protein interactions (PPIs) drive countless processes in biology. The ability to block these interactions with high specificity is crucial for probing the basic science of these processes, as well as for developing imaging agents or novel therapeutics. However, most traditional molecules for blocking protein-protein interactions—like small molecules, peptides, or antibodies—rely on the precise targeting of the crucial interface or binding pocket, which can be difficult for some targets. Furthermore, none of these approaches can be easily tuned to match the valency or size of the target, and binding to patches on the protein not directly involved in PPIs can fail to block activity. Here, we propose to develop a nanoscale synthetic antibody (“nano-synbody”) consisting of a tunable DNA nanostructure bearing 2-3 peptide/protein ligands that can bind to distinct surfaces of a target protein and block its association with its partner through the steric bulk of the DNA structure. The individual peptide/protein binding agents will be derived from either known molecules, or found independently through methods like phage display. Critically, our method merges computational simulation—and in silico “evolution”—of these hybrid protein-DNA nano-synbodies, creating a library of structures and probing their association with the target. We aim to create a feedback loop, whereby the computational simulations yield candidate nano-synbodies that can be experimentally tested, further informing the next round of simulations. We will first apply this pipeline to a homo-trimeric nano-synbody against the SARS-CoV-2 spike protein trimer (Aim 1). This test bed will allow us to optimize the process and find a high-affinity blocking structure. Then, we will apply our method to nano-synbodies for blocking the assembly of fibrinogen into fibrin clots (Aim 2). The second Aim will involve phage display against fibrin to find novel binding agents, and thereby convert them into high-affinity hetero-trivalent structures. In both Aims, we will demonstrate the advantage of nano-structuring ligand presentation over simple oligomerization with flexible linkers. Taken together, our work will generate a new computational-experimental paradigm for the design of tunable, user-defined nanostructures that can present three or more peptides/proteins for binding to any protein, and blocking its association with its target. Crucially, our approach does not require binding directly to the interface, which should enable it to target a much larger range of proteins that may not be amenable to traditional approaches, large protein complexes, or mutants/variants of the targets that might escape single binding agents.