Abstract Traditional drug development has a long cycle,high cost,and low success rate.The emergence and rapid development of artificial intelligence(AI) have brought new opportunities for drug design.This paper focuses on the technical foundations,applications,challenges and response strategies of AI in drug design,including machine learning/deep learning,quantum chemistry computing and molecular docking/virtual screening.It analyzes its applications in drug target recognition/validation,drug lead compound screening/optimization and adverse drug reaction prediction.At the same time,this paper explores the challenges and response strategies faced by AI in terms of data quality,model interpretability,experimental validation and clinical translation,and shortage of professional talents,and looks forward to the development trend of AI in the field of drug design.
ZHANG Ting-Ting, YU Xiao-Yan, HUANG Cheng-Man, JIANG Xin-Yi, WANG Qi, HAI Hua, NA Li-Yan. AI-Assisted Drug Design:Technical Foundations,Applications,Challenges and Response Strategies[J]. Chinese Journal of Chemical Education, 2026, 47(14): 1-7.
