image: This figure illustrates three key applications of AI in antimicrobial drug development: (1) target identification and validation, including novel target discovery, affinity prediction, multi-target synergistic intervention, and drug repurposing; (2) hit molecule design, incorporating virtual screening(VS), high-throughput screening, and de novo molecular design techniques; (3) lead compound optimization, focusing on optimization of target spatial structures and enhancement of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties.
Credit: Kexin Li, Quan Yuan, Chang Qi, Ying Shi, Hong Yang, Anqi Lin, Shuofeng Yuan
Artificial intelligence (AI) is transforming the fight against infectious diseases and antimicrobial resistance (AMR), a global public health crisis responsible for 1.27 million direct deaths in 2019. Traditional drug development is often too slow and inefficient, taking 2-5 years and struggling to counter rapidly evolving resistance and bottlenecks like high toxicity in antiviral and antifungal therapies. AI provides a revolutionary solution by accelerating pathogen evolution prediction, enabling new target discovery, and facilitating efficient compound design and optimization. This technology aims to drastically compress the development cycle to 3-6 months by focusing on key applications like phenotype-driven target identification and validation and targeted molecule design and lead compound optimization.
Method of Research
Commentary/editorial
Subject of Research
Not applicable
Article Title
Artificial Intelligence Revolutionizes Anti-Infective Drug Discovery: From Target Identification to Lead Optimization
Article Publication Date
16-Oct-2025
COI Statement
No potential conflict of interest was reported by the authors.