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The analysis of biomolecular structures is a crucial task for a wide range of applications ranging from drug design to protein engineering. The Protein Data Bank (PDB) file format (Burley et al., 2019) is the most popular format to describe biomolecular structures such as proteins and nucleic acids. In this text-based format, each line represents a given atom and entails its main properties such as atom name and identifier, residue name and identifier, chain identifier, coordinates, etc. Several solutions have been developed to parse PDB files into dedicated objects that facilitate the analysis and manipulation of biomolecular structures. This is, for example, the case for the BioPython parser (Cock et al., 2009,@biopdb) that loads PDB files into a nested dictionary, the structure of which mimics the hierarchical nature of the biomolecular structure. Selecting a given sub-part of the biomolecule can then be done by going through the dictionary and selecting the required atoms. Other packages, such as ProDy (Bakan, Meireles, & Bahar, 2011), BioJava (Lafita, 2019), MMTK (Hinsen, 2000) and MDAnalysis (Gowers et al., 2016) to cite a few, also offer solutions to parse PDB files. However, these parsers are embedded in large codebases that are sometimes difficult to integrate with new applications and are often geared toward the analysis of molecular dynamics simulations. Lightweight applications such as pdb-tools (Rodrigues, Teixeira, Trellet, & Bonvin, 2018) lack the capabilities to manipulate coordinates.

The pdb2sql Python Package: Parsing, Manipulation and Analysis of PDB Files Using SQL Queries