International Journal of Medicine and Data

With the rapid advancement of omics technologies and structural biology, computational technologies have played an increasingly prominent role in drug design and discovery. This review provides a comprehensive overview of the current mainstream strategies in computer-aided drug design (CADD), with a particular emphasis on the application of bioinformatics approaches—such as Weighted Gene Co-expression Network Analysis (WGCNA), single-cell RNA sequencing (scRNA-seq), and machine learning—in the identification of drug targets. Additionally, structure-based techniques including virtual screening, molecular docking, molecular dynamics simulations, binding free energy calculations, and alanine scanning are highlighted for their critical roles in the screening of candidate small molecules and the elucidation of underlying mechanisms. On this basis, the integration and synergistic application of multiple computational technologies are further discussed. Finally, the future development trends and challenges of CADD under the influence of artificial intelligence and multimodal data are explored. This study aims to provide theoretical support and technical reference for novel drug development in interdisciplinary contexts.

Computer-aided drug design; WGCNA; scRNA-seq; Virtual screening; Molecular dynamics simulations; Binding free energy calculations; Alanine scanning