人工智能（AI）和机器学习不仅使药物发现和开发实现了质的飞跃，而且帮助药物开发进程进入现代化。机器学习和深度学习算法已应用于药物发现各个阶段，如先导化合物的筛选、多肽合成及小分子药物的发现、最佳给药剂量的确定、类药化合物的设计和药物不良反应的预测、蛋白质间相互作用的预测、虚拟筛选效率的提高、定量构效关系（QSAR）建模和药物重新定位、理化性质和药物靶标亲和力的预测、化合物的结合预测和体内安全性分析、多靶点配体药物分子的设计以及临床试验的设计。简要综述了AI算法和传统化学相结合以提高药物发现的效率以及AI在药物发现过程中的应用研究进展，以期为AI应用于药物发现提供一定参考。

Artificial intelligence (AI) and machine learning (ML) not only has made a qualitative leap in drug discovery and development, but also has helped the process of drug development enter modernization. Algorithms of ML and deep learning (DL) have been applied to various phases of drug discovery, such as screening of lead compounds, peptide synthesis and discovery of small molecular drugs, determination of the optimal dosage, design of drug-like compounds and prediction of adverse drug reaction (ADR), prediction of protein-protein interaction, improvement of the efficiency of virtual screening, quantitative structure-activity relationship (QSAR) modeling and drug repositioning, prediction of physicochemical properties and affinity of drug targets, prediction of drug binding and in vivo safety analysis, design of multiple target ligand drug molecules, as well as design of clinical trials. The research progress in the combination of AI algorithm and traditional chemistry to improve the efficiency of drug discovery and application of AI during the process of drug discovery was briefly reviewed, in order to provide some references for using AI for drug discovery in China.

中国食品药品检定研究院学科带头人课题（2021X2）