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

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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.