Computational design of self-assembling proteins and protein-DNA nanowires

Computational protein design (CPD) is a burgeoning field that uses a physical-chemical or knowledge-based scoring function to create protein variants with new or improved properties. This exciting approach has recently been used to generate proteins with entirely new functions, ones that are not observed in naturally occurring proteins. For example, several enzymes were designed to catalyze reactions that are not in the repertoire of any known natural enzyme. In these designs, novel catalytic activity was built de novo (from scratch) into a previously inert protein scaffold. In addition to de novo enzyme design, the computational design of protein-protein interactions can also be used to create novel functionality, such as neutralization of influenza. Our goal here was to design a protein that can self-assemble with DNA into nanowires. We used computational tools to homodimerize a transcription factor that binds a specific sequence of double-stranded DNA. We arranged the protein-protein and protein-DNA binding sites so that the self-assembly could occur in a linear fashion to generate nanowires. Upon mixing our designed protein homodimer with the double-stranded DNA, the molecules immediately self-assembled into nanowires. This nanowire topology was confirmed using atomic force microscopy. Co-crystal structure showed that the nanowire is assembled via the desired interactions. To the best of our knowledge, this is the first example of a protein-DNA self-assembly that does not rely on covalent interactions. We anticipate that this new material will stimulate further interest in the development of advanced biomaterials.

Scalable Methods for Deterministic Integration of Quantum Emitters in Photonic Crystal Cavities

We investigated four unique methods for achieving scalable, deterministic integration of quantum emitters into ultra-high Q{V photonic crystal cavities, including selective area heteroepitaxy, engineered photoemission from silicon nanostructures, wafer bonding and dimensional reduction of III-V quantum wells, and cavity-enhanced optical trapping. In these areas, we were able to demonstrate site-selective heteroepitaxy, size-tunable photoluminescence from silicon nanostructures, Purcell modification of QW emission spectra, and limits of cavity-enhanced optical trapping designs which exceed any reports in the literature and suggest the feasibility of capturing- and detecting nanostructures with dimensions below 10 nm. In addition to process scalability and the requirement for achieving accurate spectral- and spatial overlap between the emitter and cavity, these techniques paid specific attention to the ability to separate the cavity and emitter material systems in order to allow optimal selection of these independently, and eventually enable monolithic integration with other photonic and electronic circuitry.

We also developed an analytic photonic crystal design process yielding optimized cavity tapers with minimal computational effort, and reported on a general cavity modification which exhibits improved fabrication tolerance by relying exclusively on positional- rather than dimensional tapering. We compared several experimental coupling techniques for device characterization. Significant efforts were devoted to optimizing cavity fabrication, including the use of atomic layer deposition to improve surface quality, exploration into factors affecting the design fracturing, and automated analysis of SEM images. Using optimized fabrication procedures, we experimentally demonstrated 1D photonic crystal nanobeam cavities exhibiting the highest Q/V reported on substrate. Finally, we analyzed the bistable behavior of the devices to quantify the nonlinear optical response of our cavities.