Chapter title |
Empowering the Potential of Cell-Penetrating Peptides for Targeted Intracellular Delivery via Molecular Self-Assembly
|
---|---|
Chapter number | 12 |
Book title |
Peptides and Peptide-based Biomaterials and their Biomedical Applications
|
Published in |
Advances in experimental medicine and biology, January 2017
|
DOI | 10.1007/978-3-319-66095-0_12 |
Pubmed ID | |
Book ISBNs |
978-3-31-966094-3, 978-3-31-966095-0
|
Authors |
Yejiao Shi, João Conde, Helena S. Azevedo |
Abstract |
Cell-penetrating peptides (CPPs) have been widely explored as an effective tool to deliver a variety of molecules and nanoparticles into cells due to their intrinsic property to translocate across cell membranes. CPPs are easier to synthesize and functionalize, and their incorporation into delivery vehicles could be achieved by both non-covalent and covalent methods. Recent advances in molecular self-assembly have demonstrated the possibility to fabricate various nanostructures with precise control over the shape, size and presentation of diverse functionalities. Through rational design, CPPs could be used as a building block for the nanostructure formation via self-assembly, while providing the functionality for intracellular delivery. In this book chapter, we will describe strategies to design self-assembling CPP conjugates and illustrate how their self-assembled nanostructures are manipulated for effective intracellular delivery. Fundamental knowledge on CPPs and molecular self-assembly will also be described. |
X Demographics
Geographical breakdown
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Portugal | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 5 | 42% |
Professor | 1 | 8% |
Student > Ph. D. Student | 1 | 8% |
Lecturer > Senior Lecturer | 1 | 8% |
Unknown | 4 | 33% |
Readers by discipline | Count | As % |
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Chemistry | 2 | 17% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Computer Science | 1 | 8% |
Agricultural and Biological Sciences | 1 | 8% |
Medicine and Dentistry | 1 | 8% |
Other | 1 | 8% |
Unknown | 5 | 42% |