Computationally designed ssDNA modular nanorobots for cancer recognition, toehold disintegration, visual diagnosis and synergistic gene silencing

Abstract Single-stranded DNA (ssDNA) allows more flexible and directional modifications than relatively rigid double-stranded DNA (dsDNA) in a ‘side-by-side’ manner. However, ssDNA applications are greatly limited by their poor stability from the ‘atom equivalents’ design, suffering from increased folding errors and complicated sequence optimizations. Herein, via all-atom molecular dynamics (MD) simulations, a molecular dynamics simulation of the dynamic folding of ssDNA in the self-assembly process was examined and optimized. This guided the intelligent construction of a stable frame structure of tetrahedral ssDNA modular nanorobots, which are convenient for diagnosis and therapy applications. The ssDNA modular nanorobots were assembled with five functional modules, which included tetrahedron skeleton fixation, tumour cell membrane protein dual recognition, enzyme loading, dual-targeted miRNA detection and synergy siRNA loading. As demonstrated, the ssDNA modular nanorobots were stable, flexible, and highly utilized, and had low folding errors. For intracellular delivery, a two-aptamer logic gate was constructed for tumour cell membrane protein dual recognition, obtaining efficient and cancer-selective internalization of ssDNA nanorobots with reagent loading. Then, in cancer cells with high expression of target miRNAs (miR-21 and miR-224), toehold disintegration was initiated by two RCA reactions for precise and visualized dual detection. Simultaneously, the released disintegrated modules triggered synergistic gene silencing by two loaded siRNAs, which resulted in a 95.6% cure rate in 17 days. This work has provided a computationally designed pathway for constructing flexible ssDNA modular nanorobots, showing better multiflexibility and applicability than relatively rigid dsDNA nanostructures.