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Programming Designer DNA Origami Wireframe Nanostructures

Nature has developed ways to organize macromolecules at the nanometer scale for a variety of purposes, from bacterial chromatophores arranging light harvesting complexes to funnel energy to reaction centers, to viral capsids encapsulating and delivering genetic information in a targeted manner into cells. DNA nanoparticles offer the ability to achieve similar functionality: due to the specificity of self-assembly, the positions and orientations of each nucleotide, and any molecules bound to them, are well-defined. Deriving the rules for DNA self-assembly can allow not only a deeper understanding and reverse engineering of existing assemblies but also the extension of the design space to structures beyond the set of naturally evolved molecules. Towards this aim, we have developed a top-down sequence design approach based on the principle of scaffolded DNA origami DAEDALUS (DNA Origami Sequence Design Algorithm for User-defined Structures) (Veneziano, Ratanalert, et al. Science, 2016). We present a fully autonomous algorithm to produce a single-stranded DNA scaffold and complementary staple strands, which can fold into nearly arbitrary target 3D objects, from Platonic solids to non-spherical topologies. Several structures were demonstrated experimentally with near quantitative yield and reconstructed in 3D using cryo-electron microscopy. Recently, we have developed the design of DNA origami with not only anti-parallel (DX) but also parallel crossover (PX) motifs, which offers the ability to program a single DNA molecule to fold into these arbitrary 3D shapes on its own, similar to natural RNA assemblies, and can potentially lead to in vivo synthesis of DNA origami (Ratanalert et al., in prep, 2017). In addition, we are investigating the underlying thermodynamics of these nanoparticles using quantitative PCR to track fluorescence with temperature, with which we can understand the effects of design choices, such as scaffold routing, on the transition temperature of the structure. Developing a simple model would potentially not only allow for optimization of new designs but also for reduction in annealing times by shortening cooling time in noncritical temperature regions. These algorithms and developments in synthesis resolve the challenge in synthetic structural biology to program and functionalize nearly arbitrary 3D nanostructures.

Sakul Ratanalert

Laboratory for Computational Biology and Biophysics
Department of Biological Engineering and Department of Chemical Engineering
Massachusetts Institute of Technology, Cambridge, MA

Created November 13, 2017, Updated October 27, 2020