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Cited by 1,057

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Self-assembled peptide nanostructures: the design of molecular building blocks and their technological utilization

Gazit, Ehud·2007·Chemical Society Reviews

Abstract

In this tutorial review the process and applications of peptide self-assembly into nanotubes, nanospheres, nanofibrils, nanotapes, and other ordered structures at the nano-scale are discussed. The formation of well-ordered nanostructures by a process of self-association represents the essence of modern nanotechnology. Such self-assembled structures can be formed by a variety of building blocks, both organic and inorganic. Of the organic building blocks, peptides are among the most useful ones. Peptides possess the biocompatibility and chemical diversity that are found in proteins, yet they are much more stable and robust and can be readily synthesized on a large scale. Short peptides can spontaneously associate to form nanotubes, nanospheres, nanofibrils, nanotapes, and other ordered structures at the nano-scale. Peptides can also form macroscopic assemblies such as hydrogels with nano-scale order. The application of peptide building blocks in biosensors, tissue engineering, and the development of antibacterial agents has already been demonstrated.

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Metadata

Authors
Gazit, E.
Venue
Chemical Society Reviews
Published
2007
Volume
36
Issue
8
Pages
1263
ISSN
  • 0306-0012 (ISSN-L)
  • 1460-4744
OpenAlex
W2322972210
Cited by
1,057
References
2
FWCI
1.89
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Self-assembled peptide nanostructures: the design of molecular building blocks and their technological utilization. https://app.cochat.ai/papers/10.1039/b605536m
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Gazit, E. (2007). Self-assembled peptide nanostructures: the design of molecular building blocks and their technological utilization. Chemical Society Reviews. https://doi.org/10.1039/b605536m

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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.