Bioinformatics plays a crucial role in computer-aided drug design (CADD) by providing tools and databases that facilitate the identification, optimization, and prediction of potential drug candidates. These computational resources allow researchers to analyze vast amounts of biological and chemical data, accelerating drug discovery while reducing costs and experimental trial-and-error. One of the primary ways bioinformatics supports CADD is through access to databases that store information on protein sequences, structures, chemical compounds, and pharmacological properties. For example, databases such as Protein Data Bank (PDB) provide three-dimensional structures of proteins, while PubChem and ChEMBL catalog chemical structures and bioactivity data. These resources form the foundation for both structure-based and ligand-based drug design approaches. In structure-based drug design, the knowledge of the target protein’s three-dimensional structure is used to identify potential binding sites and design molecules that can interact optimally with the target. Bioinformatics tools enable molecular docking, where candidate ligands are computationally fitted into the active site of the protein to predict