Localized Catalytic DNA Circuits for Integrated Information Processing in Molecular Machines

This thesis supports the long-term goal of engineering molecular devices with computational complexity akin to cells. Like cells, artificial molecular devices can benefit from integrating multiple computational modalities. To that end, this thesis advances molecular computing systems in three modalities: dynamic molecular assembly, well-mixed circuits, and spatially-organized cascades. Specifically, it introduces methods to enhance control over DNA structural assembly, well-mixed DNA circuits, and DNA circuits localized to a DNA origami surface. As DNA structural assembly grows increasingly complex, so too grows the potential for off-target structures. This issue can be addressed through developmental self-assembly, where components join a growing structure in a programmed sequence under controlled kinetics. The scope of developmental self-assembly is here expanded by a method enabling specific pathway selection among multiple encoded options. Well-mixed DNA circuits require catalytic motifs for signal restoration and amplification. A catalytic motif is presented where two input strands cooperate to control catalysis. This motif could enhance AND gates and thresholding, and could enable adaptive memories and learning behaviors in DNA-based neural networks. Localized DNA circuits lack cascadable catalytic mechanisms for signal restoration and amplification. Two designs for a localized catalytic mechanism are presented. Each omits any intermediate diffusible species to support nanodevices compatible with uncontrolled environments, as in biomedical contexts. This constraint leads to design lessons; principally, we respond to leak in the first design through geometric constraints in the second design.