ABPDB: A Database of Antibacterial Peptides

Area of Science:

• Biochemistry
• Bioinformatics
• Drug Discovery

Background:

• Antimicrobial resistance (AMR) is a growing global health threat.
• Antibacterial peptides (ABPs) represent a promising alternative to conventional antibiotics.
• Existing ABP resources are fragmented, hindering comprehensive research.

Purpose of the Study:

• To create a centralized and comprehensive database of antibacterial peptides.
• To facilitate research into novel antibacterial peptide discovery and development.
• To provide tools for analyzing ABP properties and structures.

Main Methods:

• Integrated data from multiple existing ABP databases.
• Collected sequence, activity, physicochemical, and structural information for 4,872 ABPs.
• Predicted 3D structures using AlphaFold2.
• Developed a structural similarity search service.

Main Results:

• Launched the AntiBacterial Peptides DataBase (ABPDB) with 4,872 curated ABPs.
• ABPDB includes detailed sequence, activity, physicochemical, and predicted 3D structural data.
• A functional service for identifying structurally similar peptides is available.

Conclusions:

• ABPDB offers a valuable, user-friendly resource for the scientific community.
• The database supports the development of new strategies against antimicrobial resistance.
• Freely accessible at http://www.acdb.plus/ABPDB, ABPDB promotes further research and innovation.