Modeling DNA Origami Self Assembly and Organization at Long Length and Time Scales

Abstract

DNA nanotechnology is a fascinating field that eschews using DNA as an information storage medium and instead uses it as a nanoscale structural material, taking advantage of the canonical base pairing rules to fold DNA into shapes, patterns, and mechanical devices 10,000 times smaller than a human hair. Over the 40 years of the field's existence, DNA nanotechnology has progressed from building simple wireframe structures to a full-blown nanoengineering ecosystem with the ability to construct logic-gated nanoscale drug delivery vehicles, computing devices, robots, and more. Key to the development of the field has been the growing ability to predict the behavior of DNA nanostructures. However, much is still not understood these devices' self-assembly and dynamic behaviors. The reason for this is that DNA interacts on a short length scale and a long timescale, and many processes occur far from equilibrium, both of which make modeling their behavior challenging. This dissertation presents three projects employing mesoscopic simulations, statistical mechanics, and numerical free energy landscape calculations to provide access to these length and time scales in order to better understand the self-assembly and organization of DNA nanostructures. Specifically, mesoscopic simulations are used to directly simulate the self-assembly of DNA nanostructures and understand the mechanism of their folding; lattice simulations are used to understand the phase behavior of arrays of molecular rotors made from DNA; and geometric calculations and Brownian dynamics simulations are used to computationally derive a bottom-up technique for templating heterogeneous DNA origami species on a single lithographically-defined template.