Addressing antimicrobial resistance by using macrocyclic peptides

Antimicrobial resistance (AMR) is a global health problem, therefore, anti-AMR alternatives and strategies are required to develop effective therapeutics. Bearing this in mind, macrocyclic peptides (MCPs) that present cyclic scaffolds, disulfide bonds and constrained arrangements offer a distinct structural advantage that expands their potential mechanisms of action against pathogens. By modifying and improving this class of peptides, it is possible to obtain greater stability under extreme biological conditions and extended therapeutic windows, also enabling targeted action against intracellular pathogens. These advancements are driven by integrating computational tools, including artificial intelligence, to predict optimal sequences based on amino acid motifs, patterns, and physicochemical properties. Altogether, these approaches help us to design optimised MCPs and facilitate the development of more robust, selective and effective therapeutic agents tailored to combat AMR. In this review, we will explore recent advances in the context of AMR, integrating computational approaches for MCPs design, and proposed mechanisms of action for the next generation of MCP-based therapeutics.