Algorithmic Design of Biomolecular Nanostructures

Biomolecular nanotechnology, a field where biomolecules such as DNA and RNA are used as programmable nanoscale construction materials, is emerging as a breakthrough technology with promising applications in nanomedicine, materials science and biophysical research. To accelerate the developments in nucleic acid nanotechnology, general and automated computer aided design tools which enable researchers from different fields to quickly design and synthesize nucleic acid nanostructures could play a significant role. Working in the framework of the robust DNA origami approach, this dissertation presents a novel, highly general and highly automated design approach for the design and synthesis of 2D and polyhedral DNA nanostructures suitable for e.g. biomedical applications. Grounded on graph-theoretic principles, the method introduces an Eulerian tour based approach for topologically routing DNA strands into nanoscale geometries exhibiting complex features. By employing an implementation of the design method, the impact of wireframe architecture on material efficiency and stiffness of DNA nanoscale assemblies was experimentally investigated. Motivated by the design of wireframe DNA nanostructures, we develop an algorithm for finding unknotted DNA strand routings on topologically more complex higher-genus mesh wireframes. Alternatively, cotranscriptionally folding RNA nanostructures have great potential for cell-based mass production of nucleic acid nanostructures. However, the presence of the cotranscriptional complex can present obstacles to folding a target shape. In this dissertation, we propose a graph-theoretic design framework which minimizes the risk of folding traps in a cotranscriptional setting.