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Artificial intelligence (AI) technology is revolutionizing antimicrobial drug development. In response to increasingly severe antimicrobial resistance challenges, AI can efficiently predict pathogen evolutionary trends, identify potential drug targets, and accelerate compound design and optimization, thereby significantly shortening the development timeline for antimicrobial agents. This correspondence focuses on the applications of AI in phenotype-driven target identification and validation, rational molecular design, and lead compound optimization for antimicrobial drug development, while highlighting current limitations and providing perspectives on future directions.
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Li et al. (2025) studied this question.
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