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Development and Challenges of Antimicrobial Peptides for Therapeutic Applications

Open access
Chen, Charles H., Lu, Timothy K.·2020·Antibiotics

Abstract

More than 3000 antimicrobial peptides (AMPs) have been discovered, seven of which have been approved by the U.S. Food and Drug Administration (FDA). Now commercialized, these seven peptides have mostly been utilized for topical medications, though some have been injected into the body to treat severe bacterial infections. To understand the translational potential for AMPs, we analyzed FDA-approved drugs in the FDA drug database. We examined their physicochemical properties, secondary structures, and mechanisms of action, and compared them with the peptides in the AMP database. All FDA-approved AMPs were discovered in Gram-positive soil bacteria, and 98% of known AMPs also come from natural sources (skin secretions of frogs and toxins from different species). However, AMPs can have undesirable properties as drugs, including instability and toxicity. Thus, the design and construction of effective AMPs require an understanding of the mechanisms of known peptides and their effects on the human body. This review provides an overview to guide the development of AMPs that can potentially be used as antimicrobial drugs.

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Metadata

Authors
Chen, C. H., & Lu, T. K.
Venue
Antibiotics
Publisher
MDPI AG
Published
2020-01-13
Volume
9
Issue
1
Pages
24
ISSN
2079-6382 (ISSN-L)
OpenAlex
W2999569426
Cited by
598
References
3
FWCI
47.20
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Development and Challenges of Antimicrobial Peptides for Therapeutic Applications. https://app.cochat.ai/papers/10.3390/antibiotics9010024
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Chen, C. H., & Lu, T. K. (2020). Development and Challenges of Antimicrobial Peptides for Therapeutic Applications. Antibiotics. https://doi.org/10.3390/antibiotics9010024

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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.