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Cited by 719

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Control of Self-Assembly of DNA Tubules Through Integration of Gold Nanoparticles

Open access
Sharma, Jaswinder, Chhabra, Rahul, Cheng, Anchi, Brownell, Jonathan, Liu, Yan, Yan, Hao·2009·Science

Abstract

The assembly of nanoparticles into three-dimensional (3D) architectures could allow for greater control of the interactions between these particles or with molecules. DNA tubes are known to form through either self-association of multi-helix DNA bundle structures or closing up of 2D DNA tile lattices. By the attachment of single-stranded DNA to gold nanoparticles, nanotubes of various 3D architectures can form, ranging in shape from stacked rings to single spirals, double spirals, and nested spirals. The nanoparticles are active elements that control the preference for specific tube conformations through size-dependent steric repulsion effects. For example, we can control the tube assembly to favor stacked-ring structures using 10-nanometer gold nanoparticles. Electron tomography revealed a left-handed chirality in the spiral tubes, double-wall tube features, and conformational transitions between tubes.

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Crossref · 10.1126/science.1165831

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Metadata

Authors
Sharma, J., Chhabra, R., Cheng, A., Brownell, J., Liu, Y., & Yan, H.
Venue
Science
Published
2009-01-02
Volume
323
Issue
5910
Pages
112-116
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1992810019
Cited by
719
References
1
FWCI
31.93
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Control of Self-Assembly of DNA Tubules Through Integration of Gold Nanoparticles. https://app.cochat.ai/papers/10.1126/science.1165831
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Sharma, J., Chhabra, R., Cheng, A., Brownell, J., Liu, Y., & Yan, H. (2009). Control of Self-Assembly of DNA Tubules Through Integration of Gold Nanoparticles. Science. https://doi.org/10.1126/science.1165831

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.