Toward Robust DNA Strand Displacement Circuits through Systematic Multi-Objective Design Optimization

Abstract

Molecular computation using biochemical components offers a path toward programming and control of matter at the molecular level. Nucleic acid strand displacement circuits have emerged as a powerful substrate for systems spanning molecular signal transduction, logic, and dynamic chemical reaction networks. Yet despite major advances, practical deployment remains constrained by off-target interactions and other operational failure modes. This dissertation advances a robustness-by-design framework for molecular computation by addressing four major classes of failure modes through three complementary optimization strategies spanning network architecture, sequence-level encoding, and chemical alphabet choice. These include sequence-level optimization layered onto existing leak-suppressing circuit architectures to reduce spurious interactions, expanded chemical alphabets for tuning molecular orthogonality, and architectural strategies for scaling input selectivity. Across theory, simulation, and experiment, these strategies systematically improve the operational fidelity and robustness of DNA strand displacement circuits. Collectively, this work provides concrete solutions to key failure modes and a unifying framework for organizing robust molecular circuit design in programmable polymers. More broadly, it establishes a foundation for extending robust design principles to programmable sequence-defined molecular systems.