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Artificial Intelligence Revolutionizes Anti‐Infective Drug Discovery: From Target Identification to Lead Optimization

Year: 2025

Type: article

Abstract: 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.

Source: iMetaMed

DOI: 10.1002/imm3.70011

Authors: Kexin Li, Quan Yuan, Chang Qi, Ying Shi, Hong Yang, Anqi Lin, Shuofeng Yuan

Institutions: Zhujiang Hospital, Southern Medical University, University of Hong Kong, TU Wien, Hong Kong Science and Technology Parks Corporation

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4415273452

FWCI: 1.922

Cites: 21

Cited by: 4

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