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Optimising DNA origami assembly by reducing off-target interactions

Lookup NU author(s): Dr Benjamin Shirt-Ediss, Dr Emanuela TorelliORCiD, Dr Silvia NavarroORCiD, Kai Armstrong, Professor Natalio KrasnogorORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© The Author(s) 2026. DNA origami enables the programmable self-assembly of nucleic acids into precisely defined nanostructures, yet the influence of primary base sequence on folding reliability remains incompletely understood. In particular, off-target interactions between scaffold and staple strands may introduce kinetic traps and reduce assembly yield, even when the intended Watson-Crick complementarity is preserved. Here we show that scaffold sequence strongly affects DNA origami assembly through the prevalence of off-target binding reactions implicit in the chosen base sequence. We developed a multi-objective computational framework that scores candidate scaffold sequences according to four classes of off-target interactions and selects variants predicted to minimise these effects for a given origami design. Using this approach, we identified both favourable and unfavourable scaffold regions from biological and synthetic sequences and tested them experimentally across 2D and 3D DNA origami structures. Atomic force microscopy showed that scaffolds predicted to have fewer off-target interactions consistently folded with higher yield, whereas off-target-prone scaffolds largely failed despite having fully complementary staple sets. Single-molecule optical tweezers further revealed that scaffold variants with fewer predicted off-target interactions assemble into more mechanically uniform origami structures. These results establish off-target sequence effects as a major determinant of origami folding and we provide a software tool to select scaffold sequences that minimise off-target reactions for any DNA origami design.


Publication metadata

Author(s): Shirt-Ediss B, Torelli E, Navarro SA, Khamis H, Kaplan A, Trewby W, Elezgaray J, Moradzadeh N, Haydell M, Keppner D, Famulok M, Armstrong K, Krasnogor N

Publication type: Article

Publication status: Published

Journal: Nature Communications

Year: 2026

Volume: 17

Online publication date: 26/05/2026

Acceptance date: 08/05/2026

Date deposited: 04/08/2026

ISSN (electronic): 2041-1723

Publisher: Springer Nature

URL: https://doi.org/10.1038/s41467-026-73387-4

DOI: 10.1038/s41467-026-73387-4

Data Access Statement: Gels (uncropped) source data are provided with this paper in a source data file, other data are available via the supplementary information file. Computed data (e.g., Fig. 1 (e, f), 3 (b, c, d, e)) are fully reproducible via the Python source code provided. A Matlab file that contains optical tweezers data has been deposited in Zenodo at https://doi.org/10.5281/zenodo.19347172. Electronic scadnano designs (.sc) of all DNA origamis used in the paper, DNA sequences used and scaffold selector HTML reports for all DNA origamis in the paper are available at Zenodo https://doi.org/10.5281/zenodo.17273772. Source data is available for Figs. 4, 5, 6, 7c–d in the associated source data file. Source data are provided with this paper.

PubMed id: 42191678


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Funding

Funder referenceFunder name
Department for Science, Innovation and Technology (DSIT)
Israel Science Foundation grant 937/20
Horizon 2020 project "AI-enabled RNA nanotechnology DElivery SysTem for INformATION transfer into cells" grant agreement 899833
Royal Academy of Engineering Chair in Emerging Technologies award
Royal Society International Exchanges grant IES/R1/180080

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