2D Peptide and Protein Crystal Engineering for Functional Materials

非技术总结：二维（2D）纳米材料（纳米片）在构建具有重要技术意义的设备方面具有潜在的优势，例如化学传感器、诊断、选择性渗透膜、催化和电子支架。然而，控制生长和合理修饰这些材料的合成结构的方法有限，这是该领域进展的重大障碍。肽和蛋白质是构建这些类型的二维材料的有吸引力的候选者，因为序列的控制可能允许跨长度尺度的结构和功能的控制。一个复杂的因素是蛋白质通常表现出复杂的折叠途径，这通常会导致对最终材料结构的控制有限。提出了一种方法，其中蛋白质数据库（PDB）的结构信息，一个免费提供的大量高分辨率蛋白质结构库，将被用作创建新型基于蛋白质的二维材料的起点。层状蛋白质结构将在PDB中被识别，其中层内观察到紧密接触，层间观察到长接触。计算和合理的设计方法将用于加强层内的相互作用，并进一步削弱或废除层之间的相互作用。使用这种方法，人们不需要根据第一原理明确地设计结构，而是可以用已经证明倾向于形成二维层的蛋白质来创建纳米片。将研究从潜在应用的角度来看有用的几种材料目标，包括选择性渗透膜和极性二维晶体。这些初步研究将验证计算设计方法，并提供普遍适用的方法来获取新型结构定义的二维材料。参与该项目的学生将获得跨领域研究的宝贵经验，使技能集垂直巩固，包括计算设计，合成和高分辨率结构表征的先进方法，这些将用于设计和制造功能二维纳米材料。此外，与所提议的研究相关的材料将作为内容呈现，以阐明概念和学习目标，在埃默里大学新开发的大分子化学入门本科讲座课程和实验室经验。技术概述：提出了一种启发式方法来设计结构有序的二维肽纳米材料，该方法利用蛋白质数据库（PDB）中晶体结构的自然多样性。PDB代表了丰富的生物分子结构信息宝库。许多结构包括生物分子层，即，其中接触区域在至少一个晶体学定义的平面内比平面之间更广泛的排列。原则上，在适当选择的晶体结构内的横向界面可以通过计算优化来增强原聚体之间的内聚相互作用，而轴向相互作用可以通过削弱或阻断层合而减弱。本研究包括一个原理证明，即晶体学表征的层状结构可以作为通过计算优化原聚体界面来设计和结构多样化结晶二维肽和蛋白质组装的起点。本提案的研究计划包含三个具体目标，以支持上述假设。前两个目标侧重于验证这种计算驱动的方法，以设计两种特定类别的2D肽材料目标，代表高附加值应用的潜在底物，即开放框架（多孔）晶格和极性2D晶体。我们预计这两个目标的成功将在实验上验证这种方法在材料设计方面的可行性和范围，同时为新型二维纳米材料提供途径。在第三个具体目标中，由具体目标1和2中生成的材料产生的结构数据将被用作额外计算设计的输入，以创建多组分二维纳米结构，其中构造在纳米尺度上具有化学可区分性和可独立寻址。在每个特定目标中，计算方法将首先用于优化蛋白质之间的结构关键界面。候选肽将使用高通量、低分辨率的实验方法合成和筛选。合适的结构将进行高分辨率结构分析，主要使用低温电镜二维重建和直接电子检测，并在适用时进行单晶衍射分析。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Non-technical Summary: Two-dimensional (2D) nanomaterials (nanosheets) have potential advantages for the construction of devices of technological importance, such as chemical sensors, diagnostics, selectively permeable membranes, and catalytic and electronic scaffolds. However, the limited methods to control growth and rationally modify the resultant structures of these materials represents a significant impediment to progress in this field. Peptides and proteins are attractive candidates for the construction of these types of 2D materials since the control of sequence potentially permits the control of structure and function across length scales. One complicating factor is that proteins commonly display complex folding pathways, which can often result in limited control over the structure of the final material. An approach is proposed in which structural information from the Protein Data Bank (PDB), a vast library of freely available high-resolution protein structures, will be employed as the starting point to create novel classes of protein-based 2D materials. Layered protein structures will be identified in the PDB, in which close contacts are observed within the layer and long contacts are observed between layers. Computational and rational design methods will be used to strengthen interaction within a layer and further weaken or abrogate interactions between layers. Using this approach, one need not explicitly design the structure from first principles, but can instead create nanosheets from proteins that have a demonstrated propensity to form 2D layers. Several classes of materials targets will be investigated that would be useful from the perspective of potential applications in devices, including selectively permeable membranes and polar 2D crystals. These initial studies will validate the computational design approach and provide generally applicable methods to access novel classes of structurally defined 2D materials. Students involved in this project will gain valuable experience in cross-cutting research that enables a vertical consolidation of skill sets, including computational design, synthesis, and advanced methods of high-resolution structural characterization, that will be implemented for the design and fabrication of functional 2D nanomaterials. In addition, material related to the proposed research will be presented as content to illustrate concepts and learning objectives in a newly developed introductory undergraduate lecture course and laboratory experience on macromolecular chemistry at Emory University.Technical Summary: A heuristic approach is proposed to the design of structurally ordered 2D peptide nanomaterials that leverages the natural diversity of crystal structures in the Protein Data Bank (PDB). The PDB represents a rich trove of structural information on biomolecules. Many structures comprise layers of biomolecules, i.e., arrangements in which contact areas are more extensive within at least one crystallographically defined plane than between planes. In principle, the lateral interfaces within appropriately chosen crystal structures can be computationally optimized to enhance the cohesive interactions between protomers, while axial interactions are attentuated through weakening or blocking of the lamination of layers. This investigation comprises a proof-of-principle directed toward the hypothesis that crystallographically characterized layered structures can be used as a starting point to engineer and structurally diversify crystalline 2D peptide and protein assemblies through computational optimization of protomer interfaces. The research plan of this proposal encompasses three specific aims in support of the preceding hypothesis. The first two aims focus on the validation of this computationally-driven approach with respect to the design of two specific classes of 2D peptide materials targets that represent potential substrates for high value-added applications, namely open framework (porous) lattices and polar 2D crystals. We anticipate that success in these two aims will experimentally validate the feasibility and scope of this approach with respect to materials design, while simultaneously providing access to novel 2D nanomaterials. In the third specific aim, structural data resulting from the materials generated in specific aims 1 and 2 will be employed as input for additional rounds of computational design in order to create multi-component 2D nanostructures in which the tectons are chemically distinguishable and independently addressable on the nanoscale. In each specific aim, computational methods will be employed initially to optimize the structurally critical interfaces between protomers. Candidate peptides will be synthesized and screened using higher throughput, low-resolution experimental methods. Suitable structures will be subjected to high-resolution structural analysis, primarily using cryo-EM 2D reconstruction with direct electron detection and, when applicable, single-crystal diffraction analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.