Journal
ANNUAL REVIEW OF BIOMEDICAL ENGINEERING, VOL 23, 2021
Volume 23, Issue -, Pages 339-357Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-bioeng-010220-095711
Keywords
antimicrobial peptides; cell selectivity; microbiota; machine learning; high-throughput screening; peptide conjugates
Categories
Funding
- National Center for Complementary and Integrative Health [RO1-AT-010282]
- Ray Nesbitt Chair Endowment
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Antimicrobial peptides are a class of compounds with potential therapeutic properties that can target specific groups of bacteria. While there have been efforts to find broadly active and highly potent AMPs, designing selectively targeting AMPs remains challenging.
The rise of antibiotic-resistant strains of bacterial pathogens has necessitated the development of new therapeutics. Antimicrobial peptides (AMPs) are a class of compounds with potentially attractive therapeutic properties, including the ability to target specific groups of bacteria. In nature, AMPs exhibit remarkable structural and functional diversity, which may be further enhanced through genetic engineering, high-throughput screening, and chemical modification strategies. In this review, we discuss the molecular mechanisms underlying AMP selectivity and highlight recent computational and experimental efforts to design selectively targeting AMPs. While there has been an extensive effort to find broadly active and highly potent AMPs, it remains challenging to design targeting peptides to discriminate between different bacteria on the basis of physicochemical properties. We also review approaches for measuring AMP activity, point out the challenges faced in assaying for selectivity, and discuss the potential for increasing AMP diversity through chemical modifications.
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