From Membrane Composition to Antimicrobial Strategies: Experimental and Computational Approaches to AMP De- sign and Selectivity

02 December 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The United Nations have committed to end the epidemics of communicable diseases by 2030 (SDG Target 3.3). In contrast with this ambition, the rise of Multi Drug Resistant (MDR) and Pan Drug Resistant (PDR) bacteria poses a threat of a return to the pre-antibiotic era. It is of high priority to find new therapies that target the ESKAPEE group of pathogens and their drug-resistant strains. Antimicrobial peptides (AMPs) are an emerging class of antibiotics that hold promises of overcoming bacterial resistance by using both novel mechanisms of action as well as targeting already known pathways. The chemical space of AMPs is potentially huge and methodologies allowing the rational exploration of novel structures are highly needed. This review focuses on case studies that give novel insights about the mechanisms of action, resistance and selectivity of some relevant AMPs, exemplifying the importance of microscopic, computational and experimental tools. Particular focus will be devoted to bacterial membranes, and how AMPs can target them while sparing human plasma membranes, in order to become safer drugs. The lessons learned from the literature cases give directions towards the development of AMPs as drug products.

Keywords

antimicrobial resistance
antimicrobial peptides
plasma membrane
bacterial membrane
molecular dynamics simulation
machine learning

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