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患病细胞，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磁共振成像（MRI）可追踪的蛋白质纤维，能够提供药物。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其他化学制剂的输送，其应用范围可扩展到非医疗行业，包括个人护理、化妆品和环境修复。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建，快速筛选和表征新的功能性生物材料。该项目还将吸引来自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）参与，这些女孩传统上在STEM生物材料方面代表性不足，与下一代科学标准保持一致。通过与初创企业InSchoolApps和MakerSpace的合作，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：能够自组装成特定结构的多功能材料的制造在许多应用中具有巨大的潜力，包括药物输送和组织工程。一个挑战是递送适当的化学试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区域。ECM由组织成介观三维网络的蛋白质纤维（从纳米到微米）组成。开发一种能够进行靶向治疗和诊断或“治疗”的材料，将使人们能够同时与特定细胞接触，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驱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，目标是可预测的：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）使用我们开发的氟化氨基酸算法整合编码热稳定性和可追溯性的非规范氨基酸，超越生物多样性的限制;和3）在有组织的蛋白质纤维基底上生物矿化和有序化氧化铁纳米颗粒，导致具有磁性的图像就绪生物纳米复合材料。这一建议的智力价值依赖于开发一种新的模式，卷曲螺旋蛋白质材料的设计，计算和实验之间的循环。这将使快速迭代控制纤维组装和确定规则的卷曲螺旋纤维和纳米复合材料的设计。除了采用最先进的开源程序外，我们还将使用合成生物学来生产蛋白质，从而实现高通量筛选的合成。这项工作与材料基因组计划非常一致，因为我们将应用已经为蛋白质设计构建的计算工具，目的是制造新型生物材料，在这种情况下是纤维和无机-有机混合复合材料。所提出的材料的多功能性不仅将证明在生物医学中的应用是有用的，而且还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见解。

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.