The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Combinatorially Designed Lipid‐like Nanoparticles for Intracellular Delivery of Cytotoxic Protein for Cancer Therapy
Abstract
An efficient and safe method to deliver active proteins into the cytosol of targeted cells is highly desirable to advance protein‐based therapeutics. A novel protein delivery platform has been created by combinatorial design of cationic lipid‐like materials (termed “lipidoids”), coupled with a reversible chemical protein engineering approach. Using ribonuclease A (RNase A) and saporin as two representative cytotoxic proteins, the combinatorial lipidoids efficiently deliver proteins into cancer cells and inhibit cell proliferation. A study of the structure–function relationship reveals that the electrostatic and hydrophobic interactions between the lipidoids and the protein play a vital role in the formation of protein–lipidoid nanocomplexes and intracellular delivery. A representative lipidoid (EC16‐1) protein nanoparticle formulation inhibits cell proliferation in vitro and suppresses tumor growth in a murine breast cancer model.
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Cites
Protein Therapeutics: A Summary and Pharmacological Classification
Leader, B., Baca, Q. J., & Golan, D. E. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2399 · Cited by 2,161
Lipid-like materials for low-dose, in vivo gene silencing
Love, K. T., Mahon, K. P., Levins, C. G., Whitehead, K. A., Querbes, W., Dorkin, J. R., Qin, J., Cantley, W., Qin, L. L., Racie, T., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910603106 · Cited by 969
Tailoring nanocarriers for intracellular protein delivery
Gu, Z., Biswas, A., Zhao, M., & Tang, Y. (2011) · Chemical Society Reviews · doi:10.1039/c0cs00227e · Cited by 543
Multiparametric approach for the evaluation of lipid nanoparticles for siRNA delivery
Alabi, C. A., Love, K. T., Sahay, G., Yin, H., Luly, K. M., Langer, R., & Anderson, D. G. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1306529110 · Cited by 188
Cited by
Engineered Nanoparticles for Drug Delivery in Cancer Therapy
Sun, T., Zhang, Y. S., Pang, B., Hyun, D. C., Yang, M., & Xia, Y. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201403036 · Cited by 2,164
Efficient delivery of genome-editing proteins using bioreducible lipid nanoparticles
Wang, M., Zuris, J. A., Meng, F., Rees, H., Sun, S., Deng, P., Han, Y., Gao, X., Pouli, D., Wu, Q., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520244113 · Cited by 624
Self-citationTunable Rigidity of (Polymeric Core)–(Lipid Shell) Nanoparticles for Regulated Cellular Uptake
Sun, J., Zhang, L., Wang, J., Feng, Q., Liu, D., Yin, Q., Xu, D., Wei, Y., Ding, B., Shi, X., et al. (2015) · Advanced Materials · doi:10.1002/adma.201404788 · Cited by 486
Chen, T.-T., Yi, J.-T., Zhao, Y.-Y., & Chu, X. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.8b04457 · Cited by 462
Nanotechnology for protein delivery: Overview and perspectives
Yu, M., Wu, J., Shi, J., & Farokhzad, O. C. (2016) · Journal of Controlled Release · doi:10.1016/j.jconrel.2015.10.012 · Cited by 410
Metadata
- Authors
- Wang, M., Alberti, K., Sun, S., Arellano, C. L., & Xu, Q.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2014-02-12
- Volume
- 53
- Issue
- 11
- Pages
- 2893-2898
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2104101539
- Cited by
- 251
- References
- 4
- FWCI
- 8.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, M., Alberti, K., Sun, S., Arellano, C. L., & Xu, Q. (2014). Combinatorially Designed Lipid‐like Nanoparticles for Intracellular Delivery of Cytotoxic Protein for Cancer Therapy. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201311245
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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.
