ABSTRACT D‐amino acid substitution provides an effective strategy for optimizing antimicrobial peptides (AMPs) by enhancing their stability. However, the absence of universal rules renders traditional screening methods time‐consuming and labor‐intensive, potentially leading to reduced or complete loss of activity. Here, we curated a D‐amino acid‐substituted AMP dataset from published literature and databases. We then developed ADAPT, an AI‐based tool for predicting the functional impact of D‐amino acid substitutions, and integrated it into a high‐throughput screening pipeline for AMP optimization. Of the variants obtained through this pipeline, 80% exhibited enhanced antibacterial activity. Among these, dR2‐1 showed exceptional broad‐spectrum antimicrobial activity, reduced toxicity, and substantially improved stability. Mechanistic studies confirmed a membrane‐targeting antibacterial mode of action. Furthermore, we engineered a hydrogel delivery system that effectively treated cutaneous infections in mice. Overall, our study established an AI‐based framework for D‐amino acid substitution in AMPs, enabling the efficient discovery of potent and stable candidates with enhanced clinical translation potential.
Zhao et al. (Wed,) studied this question.