DMREF: Computationally Driven-Genetically Engineered Materials (CD-GEM)

非技术描述：能够进行靶向治疗和诊断或“治疗”的材料的开发，允许同时对接和治疗病变细胞，同时通过成像可视化正在发生的事情。强大的计算和实验工具将被用来开发能够输送药物的磁共振成像(MRI)可追踪蛋白质纤维。由此产生的生物材料将在药物输送和组织工程领域产生广泛的社会影响。从这些研究中吸取的经验教训可用于运送其他化学制剂，其应用范围扩展到非医疗行业，包括个人护理、化妆品和环境补救。这项研究将培养下一代科学家和工程师，利用计算生物学、蛋白质工程和材料科学的尖端技术来创造、快速筛选和表征新的功能生物材料。该项目还将吸引城市议会青年妇女数学和科学研究所的女孩(主要是有色人种妇女)，她们在STEM中的代表性传统上不足，涉及符合下一代科学标准的生物材料。在初创公司、InSchoolApp和MakerSpace的合作下，这些女孩将参与生物材料化学、计算机编程、三维蛋白质渲染和可视化。技术描述：可以自组装成定义结构的多功能材料的制造具有巨大的应用潜力，包括药物输送和组织工程。一个挑战是提供适当的化学制剂，并在复杂的生物环境或细胞外基质(ECM)中非侵入性地监测周围地区。ECM是由组织成介观三维网络的蛋白质纤维(从纳米到微米)组成的。一种能够进行靶向治疗和诊断或“治疗”的材料的开发将使人们能够同时与特定的细胞相互作用，同时通过可视化提供详细的功能和分子信息。我们打算通过计算来推动蛋白质纤维的设计，并通过实验分析来评估它们的物理化学性质，从而达到以下目的：1)在介观尺度上控制自组装成具有小分子识别功能的纤维；2)利用我们为氟化氨基酸开发的算法整合编码热稳定性和可追踪性的非规范氨基酸，使其超越生物多样性的极限；以及3)在有组织的蛋白质纤维基质上对氧化铁纳米颗粒进行生物矿化和有序处理，从而得到具有磁性的易于成像的生物纳米复合材料。这一提议的智力价值在于开发了一种在计算和实验之间循环的盘绕状蛋白质材料设计的新范例。这将使控制光纤组装的快速迭代成为可能，并确定卷曲光纤和纳米复合材料设计的规则。除了使用最先进的开源程序，我们还将使用合成生物学来生产高通量筛选所需的能够合成的蛋白质。这项工作与材料基因组倡议非常一致，因为我们将应用已经为蛋白质设计建立的计算工具，目的是制造新的生物材料，在这种情况下是纤维和无机-有机杂化复合材料。所提出的材料的多功能性不仅将被证明在生物医学中的应用，而且将导致对建模和设计蛋白质纤维和纳米复合材料的计算方法的基本洞察。

Non-technical Description: The development of materials capable of targeted therapy and diagnosis or "theranosis" allows for simultaneously interfacing and treating diseased cells while visualizing what is happening through imaging. Powerful computational and experimental tools will be employed to develop magnetic resonance imaging (MRI)-traceable protein fibers capable of delivering drugs. The resulting biomaterials will have broad societal impact in the field of drug delivery and tissue engineering. Lessons learned from these studies can be employed for delivery of other chemical agents with applications extending to non-medical industries including personal care, cosmetics and environmental remediation. This research will train the next generation of scientists and engineers to employ cutting edge technologies in computational biology, protein engineering and materials science to create, rapidly screen and characterize new functional biomaterials. The project will also engage girls (predominantly women of color) from the Urban Assembly Institute for Math and Science for Young Women who are traditionally underrepresented in STEM on biomaterials in alignment with the Next Generation Science Standards. In collaboration with the start-ups, InSchoolApps, and the MakerSpace, the girls will participate in biomaterials chemistry, computer programming, rendering of proteins in three dimensions and visualization.Technical description: The fabrication of multifunctional materials that can self-assemble into defined structures bears tremendous potential for a number of application including drug delivery and tissue engineering. One challenge is to deliver an appropriate chemical agent and non-invasively monitor the surrounding area amidst a complex biological milieu or extracellular matrix (ECM). The ECM is comprised of protein fibers (from the nano to microscale) organized into a mesoscopic three-dimensional network. The development of a material capable of targeted therapy and diagnosis or "theranosis" would enable one to simultaneously interface with specific cells while providing both detailed functional and molecular information through visualization. We intend to drive design of protein fibers through computation and assess through experimental analysis, their physicochemical properties with the objective to predictably: 1) control self-assembly into fibers on the mesoscale with functional capabilities of small molecule recognition; 2) integrate non-canonical amino acids that encode thermostability and traceability using our developed algorithms for fluorinated amino acids, beyond the limits of biological diversity; and 3) biomineralize and order iron oxide nanoparticles on the organized protein fiber substrates leading to image-ready bio-nanocomposites with magnetic properties. The intellectual merit of this proposal relies on developing a new paradigm for coiled-coil protein materials design that cycles between computation and experimentation. This will enable the rapid iteration for controlling fiber assembly and the identification of rules for coiled-coil fiber and nanocomposite design. In addition to employing state-of-the-art open source programs, we will also use synthetic biology to produce the proteins enabling synthesis for high-throughput screening. This work is well aligned with the Materials Genome Initiative, as we will apply the computational tools already built for protein design with the aim of fabricating novel biomaterials, in this case fibers and inorganic-organic hybrid composites. The versatility of the proposed materials will not only prove useful for applications in biomedicine, but also will lead to fundamental insight into computational methods for modeling and designing protein fibers and nanocomposites.