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The Use of Therapeutic Peptides to Target and to Kill Cancer Cells
Abstract
Peptide therapeutics is a promising field for emerging anti-cancer agents. Benefits include the ease and rapid synthesis of peptides and capacity for modifications. An existing and vast knowledge base of protein structure and function can be exploited for novel peptide design. Current research focuses on developing peptides that can (1) serve as tumor targeting moieties and (2) permeabilize membranes with cytotoxic consequences. A survey of recent findings reveals significant trends. Amphiphilic peptides with clusters of hydrophobic and cationic residues are features of anti-microbial peptides that confer the ability to eradicate microbes and show considerable anti-cancer toxicity. Peptides that assemble and form pores can disrupt cell or organelle membranes and cause apoptotic or necrotic death. Cell permeable and tumor-homing peptides can carry biologically active cargo to tumors or tumor vasculature. The challenge lies in developing the clinical application of therapeutic peptides. Improving delivery to tumors, minimizing non-specific toxic effects and discerning pharmacokinetic properties are high among the needs to produce a powerful therapeutic peptide for cancer treatment.
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Metadata
- Authors
- J. Boohaker, R., W. Lee, M., Vishnubhotla, P., M. Perez, J. L., & R. Khaled, A.
- Venue
- Current Medicinal Chemistry
- Publisher
- Bentham Science Publishers Ltd.
- Published
- 2012-06-01
- Volume
- 19
- Issue
- 22
- Pages
- 3794-3804
- ISSN
- 0929-8673
- PMC
- PMC4537071
- Cited by
- 302
- References
- 129
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
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.