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Cited by 428

The DOI matches its Crossref record; 174 of the 174 references it cites were found in a registry or an index.

Review: Lessons Learned From Clinical Trials Using Antimicrobial Peptides (AMPs)

Open access
Dijksteel, Gabrielle S., Ulrich, Magda M. W., Middelkoop, Esther, Boekema, Bouke K. H. L.·2021·Frontiers in Microbiology

Abstract

Antimicrobial peptides (AMPs) or host defense peptides protect the host against various pathogens such as yeast, fungi, viruses and bacteria. AMPs also display immunomodulatory properties ranging from the modulation of inflammatory responses to the promotion of wound healing. More interestingly, AMPs cause cell disruption through non-specific interactions with the membrane surface of pathogens. This is most likely responsible for the low or limited emergence of bacterial resistance against many AMPs. Despite the increasing number of antibiotic-resistant bacteria and the potency of novel AMPs to combat such pathogens, only a few AMPs are in clinical use. Therefore, the current review describes (i) the potential of AMPs as alternatives to antibiotics, (ii) the challenges toward clinical implementation of AMPs and (iii) strategies to improve the success rate of AMPs in clinical trials, emphasizing the lessons we could learn from these trials.

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Metadata

Authors
Dijksteel, G. S., Ulrich, M. M. W., Middelkoop, E., & Boekema, B. K. H. L.
Venue
Frontiers in Microbiology
Published
2021-02-22
Volume
12
Pages
616979-616979
ISSN
1664-302X (ISSN-L)
OpenAlex
W3131431845
Cited by
428
References
174
FWCI
36.77
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Review: Lessons Learned From Clinical Trials Using Antimicrobial Peptides (AMPs). https://app.cochat.ai/papers/10.3389/fmicb.2021.616979
The paper
Dijksteel, G. S., Ulrich, M. M. W., Middelkoop, E., & Boekema, B. K. H. L. (2021). Review: Lessons Learned From Clinical Trials Using Antimicrobial Peptides (AMPs). Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2021.616979

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.