Engineering Selectively Targeting Antimicrobial Peptides

Abstract

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.

Keywords: antimicrobial peptides; cell selectivity; high-throughput screening; machine learning; microbiota; peptide conjugates.

Figure 1

Current approaches for designing new antimicrobial peptides (AMPs) or optimizing existing ones for increased potency or improved selectivity, with examples of rational design, computational design, and high-throughput screening.

Figure 2

Characterization assays for testing activity or specificity of antimicrobial compounds. (a) Commonly used assays for measuring antimicrobial peptide (AMP) activity against individual species or strains in monoculture. (i) Broth dilution. Serial dilutions of an antimicrobial compound in liquid media are inoculated with the target bacteria. (ii) Agar diffusion. Varying doses of the antimicrobial compound are placed on agar plates inoculated with a bacterial lawn. Antimicrobial activity is measured by the zone of clearance. (iii) Metabolic activity test. A colorimetric or fluorogenic assay is used to assess metabolic activity of the target bacteria by measuring enzyme reduction of a substrate. (iv) Time-kill assay. An assay determines antimicrobial activity over time to measure rate of killing by the test compound. (b) Anaerobic culture systems designed to simulate microbiota within the human body, used to assay the AMP’s effect on microbial diversity. (i) Anaerobic batch cell culture. Small volume bioreactors are used to cultivate microbiota samples. (ii) Droplet-based cell culture. Droplet emulsions are generated using a microfluidic device to segregate a mixed microbial community and isolate low-abundance species.

Figure 3

Factors affecting minimum inhibitory concentration (MIC) determination in coculture and monoculture systems. (a) Complex interactions between two microbial species in a coculture system may affect antimicrobial peptide (AMP) sensitivity. (b) A cell in a microbial monoculture misses many of the factors affecting AMP sensitivity that are present in a microbial community.

Figure 4

Examples of modified antimicrobial peptides (AMPs). (a) Noncanonical amino acid (ncAA) incorporation. ncAAs may be incorporated through chemical synthesis or genetic code manipulation. (b) Antibiotic–peptide conjugate. (c) Antibody–peptide conjugate.