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Modular programming of interaction and geometric specificity enables assembly of complex DNA origami nanostructures

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arxiv 2502.05388 v1 pith:T67QTUCN submitted 2025-02-08 cond-mat.soft

classification cond-mat.soft
keywords complexcurvatureapproachassemblingdesigndesignsincludinginteractions
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We present a modular DNA origami design approach to address the challenges of assembling geometrically complex nanoscale structures, including those with nonuniform Gaussian curvature. This approach features a core structure that completely conserves the scaffold routing across different designs and preserves more than 70% of the DNA staples between designs, dramatically reducing both cost and effort, while enabling precise and independent programming of subunit interactions and binding angles through adjustable overhang lengths and sequences. Using cryogenic electron microscopy, gel electrophoresis, and coarse-grained molecular dynamics simulations, we validate a set of robust design rules. We demonstrate the method's utility by assembling a variety of self-limiting structures, including anisotropic shells with controlled inter-subunit interactions and curvature, and a toroid with globally varying curvature. Our strategy is both cost-effective and versatile, providing a promising and efficient solution for the synthetic fabrication of complex nanostructures.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Stochastic size control of self-assembled filaments

    cond-mat.soft 2025-07 conditional novelty 6.0 of 10

    Semiaddressable binding, where each species binds itself and the next in sequence, yields a tunable filament length distribution whose mean and width are independently controlled.

  2. Inverse Thermodynamics: Designing Interactions for Targeted Phase Behavior

    cond-mat.soft 2025-06 conditional novelty 6.0 of 10

    A graph-based design framework positions azeotropes at chosen compositions in binary patchy particle mixtures, confirmed by Gibbs-ensemble simulations.

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