Toward Precise Fabrication of Finite-Sized DNA Origami Superstructures.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Dongsheng Li, Jinyi Dong, Yihao Zhou, Qiangbin Wang
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引用次数: 0

Abstract

DNA origami enables the precise construction of 2D and 3D nanostructures with customizable shapes and the high-resolution organization of functional materials. However, the size of a single DNA origami is constrained by the length of the scaffold strand, and since its inception, scaling up the size and complexity has been a persistent pursuit. Hierarchical self-assembly of DNA origami units offers a feasible approach to overcome the limitation. Unlike periodic arrays, finite-sized DNA origami superstructures feature well-defined structural boundaries and uniform dimensions. In recent years, increasing attention has been directed toward precise control over the hierarchical self-assembly of DNA origami structures and their applications in fields such as nanophotonics, biophysics, and material science. This review summarizes the strategies for fabricating finite-sized DNA origami superstructures, including heterogeneous self-assembly, self-limited self-assembly, and templated self-assembly, along with a comparative analysis of the advantages and limitations of each approach. Subsequently, recent advancements in the application of these structures are discussed from a structure design perspective. Finally, an outlook on the current challenges and potential future directions is provided, highlighting opportunities for further research and development in this rapidly evolving field.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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