Structural Databases

Structural databases play a crucial role in computational biology by providing access to the three-dimensional organization of macromolecules, including proteins, nucleic acids, and macromolecular complexes. These databases serve as essential resources for researchers seeking to understand molecular function, design drugs, and model biological interactions at the atomic level. Unlike sequence databases, which store linear amino acid or nucleotide sequences, structural databases contain atomic coordinate data that describe the precise spatial arrangement of atoms within a molecule.

The Protein Data Bank (PDB) is the primary repository for experimentally determined macromolecular structures. It contains data derived from techniques such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM). Because these structures are based on experimental evidence, they are considered highly reliable. However, certain regions of macromolecules, particularly those that are highly flexible, may be unresolved or missing due to the limitations of experimental techniques.

The AlphaFold Database (AlphaFoldDB) represents an alternative source of structural information, providing computationally predicted models of protein structures. These models are generated using deep learning techniques, specifically the AlphaFold algorithm, which predicts protein folding with remarkable accuracy. While AlphaFoldDB provides structural insights for proteins that lack experimental structures, its predictions may contain inaccuracies in local conformations and binding sites. Thus, researchers must critically evaluate the confidence scores associated with these models before using them for functional analysis or drug design.

The Electron Microscopy Data Bank (EMDB) is a specialized repository for cryo-electron microscopy (cryo-EM) density maps. Unlike the PDB, which provides atomic coordinate models, the EMDB stores raw and processed electron density maps that can be further interpreted to build structural models. This database is particularly valuable for studying large macromolecular assemblies and dynamic protein complexes that are difficult to crystallize for X-ray diffraction studies.