Three-dimensional Structure Databases of Biological Macromolecules

Area of Science:

• Structural Biology
• Bioinformatics
• Computational Biology

Background:

• Databases of three-dimensional protein structures are essential resources for scientific research.
• These databases contain curated experimental data, metadata, and computational predictions.
• The Protein Data Bank (PDB) is the primary global archive for experimentally determined biomacromolecular structures.

Purpose of the Study:

• To describe the comprehensive resources and functionalities provided by protein structure databases.
• To highlight the role of the Protein Data Bank (PDB) and its managing consortium (wwPDB).
• To emphasize the growing importance of predicted protein structures, particularly after AlphaFold2 breakthroughs.

Main Methods:

• Curated repositories of experimentally determined protein structures with metadata.
• Information-retrieval tools for searching and accessing structural data.
• Integration with sequence databases, function databases, and analysis software.
• Inclusion of predicted three-dimensional protein structures.

Main Results:

• The Protein Data Bank (PDB) is managed by the wwPDB consortium, comprising five partner institutions.
• wwPDB partners provide tools for structure analysis, visualization, and community support.
• Specialized projects like SCOP, CATH, and ECOD classify protein domains based on PDB data.
• Advancements like AlphaFold2 are increasing the importance of predicted protein structures.

Conclusions:

• Protein structure databases are indispensable hubs for structural biologists, offering data, tools, and community engagement.
• The PDB and its associated resources facilitate a wide range of research in structural biology.
• The integration of experimental and predicted structures enhances the utility of these databases for future discoveries.