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Fmoc‐Diphenylalanine Self Assembles to a Hydrogel via a Novel Architecture Based on π–π Interlocked β‐Sheets
Open accessAbstract
The self assembly of peptide hydrogelators that carry aromatic substituents can be modeled by a novel nanocylindrical architecture. The proposed model suggests that the nanocylinders are formed by anti-parallel β-sheets interlocked by the π-stacking interactions of fluorenyl groups and phenyl rings. This explanation is consistent with the structures observed in TEM and the data obtained by a variety of spectroscopic techniques.
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Citations
Cited by
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Tao, K., Levin, A., Adler-Abramovich, L., & Gazit, E. (2016) · Chemical Society Reviews · doi:10.1039/c5cs00889a · Cited by 482
A review on nanoparticle based treatment for wound healing
Rajendran, N. K., Kumar, S. S. D., Houreld, N. N., & Abrahamse, H. (2018) · Journal of Drug Delivery Science and Technology · doi:10.1016/j.jddst.2018.01.009 · Cited by 389
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Metadata
- Authors
- Smith, A. M., Williams, R. J., Tang, C., Coppo, P., Collins, R. F., Turner, M. L., Saiani, A., & Ulijn, R. V.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2007-12-11
- Volume
- 20
- Issue
- 1
- Pages
- 37-41
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2047726172
- Cited by
- 995
- References
- 0
- FWCI
- 13.17
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Fmoc‐Diphenylalanine Self Assembles to a Hydrogel via a Novel Architecture Based on π–π Interlocked β‐Sheets. https://app.cochat.ai/papers/10.1002/adma.200701221
- The paper
- Smith, A. M., Williams, R. J., Tang, C., Coppo, P., Collins, R. F., Turner, M. L., Saiani, A., & Ulijn, R. V. (2008). Fmoc‐Diphenylalanine Self Assembles to a Hydrogel via a Novel Architecture Based on π–π Interlocked β‐Sheets. Advanced Materials. https://doi.org/10.1002/adma.200701221
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
