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Diverse and robust molecular algorithms using reprogrammable DNA self-assembly

An Author Correction to this article was published on 02 August 2019

This article has been updated


Molecular biology provides an inspiring proof-of-principle that chemical systems can store and process information to direct molecular activities such as the fabrication of complex structures from molecular components. To develop information-based chemistry as a technology for programming matter to function in ways not seen in biological systems, it is necessary to understand how molecular interactions can encode and execute algorithms. The self-assembly of relatively simple units into complex products1 is particularly well suited for such investigations. Theory that combines mathematical tiling and statistical–mechanical models of molecular crystallization has shown that algorithmic behaviour can be embedded within molecular self-assembly processes2,3, and this has been experimentally demonstrated using DNA nanotechnology4 with up to 22 tile types5,6,7,8,9,10,11. However, many information technologies exhibit a complexity threshold—such as the minimum transistor count needed for a general-purpose computer—beyond which the power of a reprogrammable system increases qualitatively, and it has been unclear whether the biophysics of DNA self-assembly allows that threshold to be exceeded. Here we report the design and experimental validation of a DNA tile set that contains 355 single-stranded tiles and can, through simple tile selection, be reprogrammed to implement a wide variety of 6-bit algorithms. We use this set to construct 21 circuits that execute algorithms including copying, sorting, recognizing palindromes and multiples of 3, random walking, obtaining an unbiased choice from a biased random source, electing a leader, simulating cellular automata, generating deterministic and randomized patterns, and counting to 63, with an overall per-tile error rate of less than 1 in 3,000. These findings suggest that molecular self-assembly could be a reliable algorithmic component within programmable chemical systems. The development of molecular machines that are reprogrammable—at a high level of abstraction and thus without requiring knowledge of the underlying physics—will establish a creative space in which molecular programmers can flourish.

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Fig. 1: Abstraction hierarchy for design and implementation of the complete 6-bit IBC tile set.
Fig. 2: Experimental protocol and implementation of the Sorting circuit.
Fig. 3: Reprogramming IBCs.
Fig. 4: Testing of the complete 6-bit IBC tile set.

Data availability

The AFM data generated and analysed here are available from the authors’ website (, as is the Python code for data analysis and DNA sequence design.

Change history

  • 02 August 2019

    An Amendment to this paper has been published and can be accessed via a link at the top of the paper.


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We thank C. Evans, A. Gopinath, B. Wei, C. Geary, R. Schulman, S. Woo, P. Rothemund and Y. Rondelez for experimental advice; R. Barish and R. Hariadi for contributing to preliminary designs for algorithmic self-assembly by SST; C. Moore, T. Stérin, C. Thachuk, P.-É. Meunier and C. Geary for discussions on theory; and L. Qian, G. Tikhomirov and P. Petersen for AFM usage. This work was supported by National Science Foundation (NSF) grants CCF-1162589 (to E.W., D.D. and D.W.), CCF-1162459 (to P.Y.), CCF-1219274 (to D.W. and D.D.), CCF-1619343 (to D.D.), CCF-0832824 and CCF-1317694 (Expeditions in Computing, to E.W.) and CCF-1317291 (Expeditions in Computing, to P.Y.), and by NASA grant NNX13AJ56G (to D.W.). C.M. was funded by the Fannie and John Hertz Foundation. F.Z. and J.H. received support from the Caltech Summer Undergraduate Research Fellowship program.

Author information




D.W., D.D., E.W. and P.Y. conceived the study. D.W., D.D. and E.W. designed the circuits and wrote the manuscript. D.W. and D.D. carried out all data analysis and experiments reported except for the nanotube nucleation/melt experiments (which were performed by J.H. and D.W.) and the unzipping and other early experimental protocols (performed by F.Z., C.M. and D.D.).

Corresponding authors

Correspondence to Damien Woods or David Doty or Erik Winfree.

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Competing interests

D.W., D.D., J.H., F.Z. and E.W. declare that they have no competing interests. P.Y. and C.M. declare competing interests: they are both listed as inventors on pending and issued patents on single-stranded tiles; and P.Y. is a co-founder of Ultivue Inc. and NuProbe Global.

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Supplementary information

Supplementary Information

This file contains Supplementary Information section A, which contains details about the IBC model, the abstract tile assembly model and proofreading, the SST binding domain schematics, DNA sequence design, data supporting design decisions, experimental methods, AFM image analysis, and the 21 implemented circuits

Supplementary Data

This file contains Supplementary Information section B, which contains sequences for the DNA systems explored in this paper

Supplementary Figures

This file contains Supplementary Information section C, four sample high-resolution AFM images of DNA nanostructures for several circuits

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Woods, D., Doty, D., Myhrvold, C. et al. Diverse and robust molecular algorithms using reprogrammable DNA self-assembly. Nature 567, 366–372 (2019).

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