NANOSCALE: Nanoscale Self-Assembled Block Copolypeptide Materials

摘要-德明-9986347 PI计划研究嵌段多肽的自组装，这种合成材料具有聚集和/或“折叠”成特定功能纳米结构的能力。内部结构和纳米颗粒形状是这些组装体的关键特征，这些组装体应该使材料在传感器技术以及药物和基因治疗学中具有特殊的应用属性。通过了解这种嵌段多肽的自组装规则，人们应该能够制备新的、定义明确的纳米结构，这些纳米结构可以针对特定的应用进行定制。PI将专注于这些嵌段共聚肽在溶液中的自组装，主要是以水为溶剂。通过与多肽一起工作，预期嵌段结构域中存在的二级结构将显著改变聚集体的结构。他们还计划探索多嵌段共聚肽（三个或更多个结构域）的纳米级自组装，其中离散结构组分的数量可能允许单个或少量链采用特定形状的特定三级（3D）结构。将嵌段共聚物可控地聚集成具有三级结构的离散复合物还有待完成，然而这种由氨基酸构成的材料在生物医学应用上肯定是无价的。例如药物和基因传递，复合物的形状有利于与不同生物表面的选择性相互作用。除了定义聚集体的纳米结构之外，嵌段共聚肽的这些相容性结构具有额外的特征，即它们可以对环境变化敏感，例如pH、溶剂或温度。这种性质可以用于构建纳米级组装复合物，当暴露于不同条件时，这些复合物将能够改变它们的形状。为了加速对这些新的复杂纳米结构的发现和理解，PI计划将自动化平行合成和处理方法与最先进的分析工具相结合，以快速筛选嵌段多肽相空间的许多参数（例如组成，序列，温度，溶剂）。这种方法的速度将允许探索具有纳米级折叠和自组装特性的高度复杂的聚合物序列，这些特性将与生物蛋白质相媲美。这种结构和功能特异性组装体在仿生学、生物矿化、组织工程、高强度纤维、极性或表面活性膜和涂层以及光电器件和传感器等领域具有广泛的应用。该项目的主要任务是（i）合成嵌段共聚肽库，（ii）加工粗聚合物以辅助自组装，（iii）快速筛选库以识别先导化合物和新结构，以及（iv）详细表征新的纳米结构材料。这些组件的成功演示将验证组合方法可以成功地应用于纳米结构材料的制备和分析。更重要的是，这种方法将允许未来探索高度复杂的仿生材料，否则仅仅因为其组成中可能的变量的数量而几乎不可能进行研究。

Abstract - Deming - 9986347The PI's plan to study the self-assembly of block copolypeptides as synthetic materials thatpossess the ability to aggregate and/or "fold" into specifically defined, functional nanostructures.The internal structure and nanoparticle shape are key features of these assemblies that shouldimpart the materials with exceptional attributes for applications in sensor technology as wellas drug and gene therapeutics. By understanding the rules by which such block copolypeptidesself-assemble, one should be able to prepare new, well-defined nanostructures that can be tailoredfor specific applications. The PI's will be focusing on the self-assembly of these blockcopolypeptides in solution, primarily with water as the solvent. By working with polypeptides,it is expected that the secondary structures present in the block domains will substantially alter thestructures of the aggregates. They also plan to explore the nanoscale self-assembly ofmultiblock copolypeptides (three or more domains), where the number of discrete structuralcomponents might allow individual or small numbers of chains to adopt specific tertiary (3D)structures of defined shape. The controlled aggregation of block copolymers into discretecomplexes with tertiary structure has yet to be accomplished, yet such materials, constructed ofamino acids, would certainly be invaluable for biomedical applications. Examples would bedrug and gene delivery, where the shape of the complexes favors selective interactions withdifferent biological surfaces. In addition to defining the nanostructure of aggregates, thesecondary structures of block copolypeptides have the added feature that they can be sensitive toenvironmental changes, such as pH, solvent or temperature. This property can be utilized for theconstruction of nanoscale assembled complexes that will be able to change their shape whenexposed to different conditions. Such features are useful for sensing applications or for programmed release of biologically active compounds in delivery applications.To accelerate the discovery and understanding of these new, complex nanostructures, the PI'splan to couple automated parallel synthesis and processing methods with state-of-the-artanalytical tools to rapidly screen the many parameters of block copolypeptide phase space (e.g.composition, sequence, temperature, solvent). The speed of this approach will allow theexploration of highly complex polymer sequences possessing nanoscopic folding and self-assemblyproperties that will rival those of biological proteins. Such structure and function specificassemblies will have wide ranging applications in the areas of biomimetics, biomineralization,tissue engineering, high strength fibers, polar or surface-active films and coatings, andoptoelectronic devices and sensors. The major tasks of this project are (i) the synthesis of block copoly peptide libraries, (ii) processing of the crude polymers to assist self-assembly, (iii) rapid screening of the libraries to identify lead compounds and novel structures, and (iv) detailed characterization of new nanostructured materials. The successful demonstration of these components will verify that combinatorial methods can be applied successfully to the preparation and analysis of nanostructured materials. More significantly, this methodology will allow the future exploration of highly complex biomimetic materials that would otherwise be near impossible to study solely because of the number of possible variables in their composition.