Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology. The main objective of structural bioinformatics is the creation of new methods of analysing and manipulating biological macromolecular data in order to solve problems in biology and generate new knowledge.
Protein structure
The structure of a protein is directly related to its function. The presence of certain chemical groups in specific locations allows proteins to act as enzymes, catalyzing several chemical reactions. In general, protein structures are classified into four levels: primary (sequences), secondary (local conformation of the polypeptide chain), tertiary (three-dimensional structure of the protein fold), and quaternary (association of multiple polypeptide structures). Structural bioinformatics mainly addresses interactions among structures taking into consideration their space coordinates. Thus, the primary structure is better analyzed in traditional branches of bioinformatics. However, the sequence implies restrictions that allow the formation of conserved local conformations of the polypeptide chain, such as alpha-helix, beta-sheets, and loops (secondary structure). Also, weak interactions (such as hydrogen bonds) stabilize the protein fold. Interactions could be intrachain, i.e., when occurring between parts of the same protein monomer (tertiary structure), or interchain, i.e., when occurring between different structures (quaternary structure).