ABSTRACT Antimicrobial peptides (AMPs) are promising alternatives to antibiotics but require precise and costly sequence control for efficacy. Synthetic polymers composed of acrylate and acrylamide offer a simpler and more time‐efficient antibacterial strategy compared to AMPs. Although their activity against Gram‐negative bacteria has been widely studied, their potential against Gram‐positive bacteria remains relatively understudied. Here, decision tree, random forest and K‐nearest neighbors classification models were applied to a dataset of synthetic polymers targeting Gram‐positive bacteria Staphylococcus aureus to extensively investigate its modes of action and streamline the development of highly effective polymers that fulfilled the recommended characteristics. The predictive characteristics of an effective antibacterial polymer against S. aureus were (ranked in descending order of feature importance) the following: (1) DP limited to 40, (2) net‐charge limited to +30, (3) hydrophobic‐to‐cationic ratio 0.6 to 1, (4) hydrophobic composition between 0.35 and 0.45, (5) cationic composition between 0.45 and 0.55, (6) cLogP in between 0 and +1.5, and (7) the inclusion of aromatic rings. These key characteristics are attributed to the unique structure of Gram‐positive bacteria, where synthetic polymers are required to effectively diffuse through the moderately anionic thick cell wall to actively disrupt the plasmic membrane by relying on strong hydrophobic interactions.
Roh et al. (Wed,) studied this question.