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Cited by 197

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Functional peptides for siRNA delivery

Open access
Tai, Wanyi, Gao, Xiaohu·2017·Advanced Drug Delivery Reviews

Abstract

Abstract siRNA is considered as a potent therapeutic agent because of its high specificity and efficiency in suppressing genes that are overexpressed during disease development. For nearly two decades, a significant amount of efforts has been dedicated to bringing the siRNA technology into clinical uses. However, only limited success has been achieved to date, largely due to the lack of a cell type‐specific, safe, and efficient delivery technology to carry siRNA into the target cells’ cytosol where RNA interference takes place. Among the emerging candidate nanocarriers for siRNA delivery, peptides have gained popularity because of their structural and functional diversity. A variety of peptides have been discovered for their ability to translocate siRNA into living cells via different mechanisms such as direct penetration through the cellular membrane, endocytosis‐mediated cell entry followed by endosomolysis, and receptor‐mediated uptake. This review is focused on the multiple roles played by peptides in siRNA delivery, such as membrane penetration, endosome disruption, targeting, as well as the combination of these functionalities. Graphical abstract Figure. No Caption available.

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Metadata

Authors
Tai, W., & Gao, X.
Venue
Advanced Drug Delivery Reviews
Publisher
Elsevier BV
Published
2017-02
Volume
110-111
Pages
157-168
ISSN
0169-409X (ISSN-L)
OpenAlex
W2516210262
Cited by
197
References
8
FWCI
1.38
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Functional peptides for siRNA delivery. https://app.cochat.ai/papers/10.1016/j.addr.2016.08.004
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Tai, W., & Gao, X. (2017). Functional peptides for siRNA delivery. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2016.08.004

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

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