Evidence map›Paper›PMID 42191678›Full record

ArticleNature communications2026

Optimising DNA origami assembly by reducing off-target interactions.

Ben Shirt-Ediss, Emanuela Torelli, Silvia Adriana Navarro, Hadeel Khamis, Ariel Kaplan, William Trewby, Juan Elezgaray, Nima Moradzadeh, Michael Haydell, Daniel Keppner and 3 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Controlling membrane tension by dynamic DNA nanorings.bioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ben Shirt-Ediss *Interdisciplinary Computing and Complex Biosystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0002-8853-0182
Emanuela Torelli *Interdisciplinary Computing and Complex Biosystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0002-3313-1088
Silvia Adriana NavarroInterdisciplinary Computing and Complex Biosystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0001-9290-1583
Hadeel KhamisFaculty of Biology and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel.
Ariel KaplanFaculty of Biology and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel.ORCID http://orcid.org/0000-0002-9731-6962
William TrewbyDurham University, Durham, UK.ORCID http://orcid.org/0000-0002-5319-8618
Juan ElezgarayCentre de Recherche Paul Pascal, CNRS, U. Bordeaux, Pessac, France.ORCID http://orcid.org/0000-0001-7356-0103
Nima MoradzadehLIMES Chemical Biology Unit, Universität Bonn, Bonn, Germany.ORCID http://orcid.org/0009-0002-2484-0621
Michael HaydellLIMES Chemical Biology Unit, Universität Bonn, Bonn, Germany.ORCID http://orcid.org/0009-0002-1025-4760
Daniel KeppnerLIMES Chemical Biology Unit, Universität Bonn, Bonn, Germany.
Michael FamulokLIMES Chemical Biology Unit, Universität Bonn, Bonn, Germany.ORCID http://orcid.org/0000-0001-5878-6577
Kai ArmstrongInterdisciplinary Computing and Complex Biosystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
Natalio KrasnogorInterdisciplinary Computing and Complex Biosystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK. natalio.krasnogor@newcastle.ac.uk.ORCID http://orcid.org/0000-0002-2651-4320

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) Grant agreement 899833Israel Science Foundation (ISF) Grant 937/20Royal Society Grant 937/20Royal Society International Exchanges Grant IES/R1/180080
6 · The paper itself

Abstract

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.

Indexed as

DNADNA NanostructuresNucleic Acid ConformationBase SequenceMicroscopy, Atomic ForceNanostructuresOptical TweezersDNA

Identifiers

PMID42191678
PMCPMC13388973

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.