The antimicrobial peptide database (APD) has evolved from its initial version in 2003 to the current APD3, which focuses on natural antimicrobial peptides (AMPs) with defined sequences and activities. The database includes 2619 AMPs from various sources, such as bacteria, archaea, protists, fungi, plants, and animals. APD3 contains detailed annotations for each peptide, including target pathogens, molecule-binding partners, post-translational modifications, and animal models. The database also provides amino acid profiles and signatures of natural AMPs, which are crucial for peptide classification, prediction, and design. Additionally, APD3 offers various searchable annotations and tools for research and education, such as peptide property calculations, classification methods, and peptide design. The database has been widely used for information search, peptide property calculations, classification method development, and peptide design, among other applications. The article highlights the importance of well-annotated AMP databases in advancing the field of antimicrobial peptides and their potential in combating antibiotic-resistant superbugs, HIV-1, and cancer.The antimicrobial peptide database (APD) has evolved from its initial version in 2003 to the current APD3, which focuses on natural antimicrobial peptides (AMPs) with defined sequences and activities. The database includes 2619 AMPs from various sources, such as bacteria, archaea, protists, fungi, plants, and animals. APD3 contains detailed annotations for each peptide, including target pathogens, molecule-binding partners, post-translational modifications, and animal models. The database also provides amino acid profiles and signatures of natural AMPs, which are crucial for peptide classification, prediction, and design. Additionally, APD3 offers various searchable annotations and tools for research and education, such as peptide property calculations, classification methods, and peptide design. The database has been widely used for information search, peptide property calculations, classification method development, and peptide design, among other applications. The article highlights the importance of well-annotated AMP databases in advancing the field of antimicrobial peptides and their potential in combating antibiotic-resistant superbugs, HIV-1, and cancer.