DNA origami is a robust assembly technique that folds a single-stranded DNA template into a target structure by annealing it with hundreds of short ‘staple’ strands1,2,3,4. Its guiding design principle is that the target structure is the single most stable configuration5. The folding transition is cooperative4,6,7 and, as in the case of proteins, is governed by information encoded in the polymer sequence8,9,10,11. A typical origami folds primarily into the desired shape, but misfolded structures can kinetically trap the system and reduce the yield2. Although adjusting assembly conditions2,12 or following empirical design rules12,13 can improve yield, well-folded origami often need to be separated from misfolded structures2,3,14,15,16. The problem could in principle be avoided if assembly pathway and kinetics were fully understood and then rationally optimized. To this end, here we present a DNA origami system with the unusual property of being able to form a small set of distinguishable and well-folded shapes that represent discrete and approximately degenerate energy minima in a vast folding landscape, thus allowing us to probe the assembly process. The obtained high yield of well-folded origami structures confirms the existence of efficient folding pathways, while the shape distribution provides information about individual trajectories through the folding landscape. We find that, similarly to protein folding, the assembly of DNA origami is highly cooperative; that reversible bond formation is important in recovering from transient misfoldings; and that the early formation of long-range connections can very effectively enforce particular folds. We use these insights to inform the design of the system so as to steer assembly towards desired structures. Expanding the rational design process to include the assembly pathway should thus enable more reproducible synthesis, particularly when targeting more complex structures. We anticipate that this expansion will be essential if DNA origami is to continue its rapid development1,2,3,17,18,19 and become a reliable manufacturing technology20.
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We thank K.V. Gothelf, M. Dong, A.L.B. Kodal, S. Helmig and S. Zhang (Department of Chemistry and Interdisciplinary Nanoscience Centre iNano, Aarhus, Denmark) for assistance with AFM imaging. This research was supported by Engineering and Physical Sciences Research Council grants EP/G037930/1 and EP/P504287/1, a Human Frontier Science Program grant RGP0030/2013, a Microsoft Research PhD Scholarship (F.D.), the ERC Advanced Grant VERIWARE (F.D. and M.K.) and a Royal Society–Wolfson Research Merit Award (A.J.T.).
Extended data figures
This file contains the nucleotide sequences.
About this article
Nature Communications (2017)