Journal of Chemistry and Chemical Research

The application of artificial intelligence (AI) in the field of drug molecule design and screening has increasingly become a key technology to improve the efficiency of drug research and development. By leveraging AI technologies such as deep learning and machine learning, researchers can quickly identify potential drug molecules from massive molecular datasets, thereby significantly shortening the research and development cycle, reducing costs, and improving hit rates. This paper explores AI-based strategies for drug molecule design and screening, analyzes the advantages and challenges of AI in drug molecule screening, and discusses how to optimize molecular design and enhance the accuracy of drug research and development by establishing effective computational models. It also focuses on the combined application of AI algorithms with traditional drug screening methods, as well as the potential technical difficulties encountered in drug discovery. In summary, the integration of artificial intelligence not only optimizes the design process of drug molecules but also provides new impetus for the development of drug screening and precision medicine.

Artificial intelligence; Drug molecule design; Molecular screening; Deep learning; Machine learning