Computation-Assisted Design of ssDNA Framework Nanorobots for Cancer Logical Recognition, Toehold Disintegration, Visual Dual-Diagnosis, and Synergistic Therapy.

Abstract

Single-stranded DNA (ssDNA) allows flexible and directional modifications for multiple biological applications, while being greatly limited by their poor stability, increased folding errors, and complicated sequence optimizations. This greatly challenges the design and optimization of ssDNA sequences to fold stable 3D structures for diversified bioapplications. Herein, the stable pentahedral ssDNA framework nanorobots (ssDNA nanorobots) were intelligently designed, assisted by examining dynamic folding of ssDNA in self-assemblies via all-atom molecular dynamics simulations. Assisted by two functional siRNAs (S1 and S2), two ssDNA strands were successfully assembled into ssDNA nanorobots, which include five functional modules (skeleton fixation, logical dual recognition of tumor cell membrane proteins, enzyme loading, dual-miRNA detection and synergy siRNA loading) for multiple applications. By both theoretical calculations and experiments, ssDNA nanorobots were demonstrated to be stable, flexible, highly utilized with low folding errors. Thereafter, ssDNA nanorobots were successfully applied to logical dual-recognition targeting, efficient and cancer-selective internalization, visual dual-detection of miRNAs, selective siRNA delivery and synergistic gene silencing. This work has provided a computational pathway for constructing flexible and multifunctional ssDNA frameworks, enlarging biological application of nucleic acid nanostructures.