LigExtract: Large-scale Automated Identification of Ligands from Protein Structures in the Protein Data Bank
Year: 2025
Type: article
Abstract: The Protein Data Bank (PDB) is an ever-growing database of three-dimensional macromolecular structures that has become a crucial resource for the drug discovery process. Exploring complexed proteins and accessing their associated ligands are essential for researchers to understand biological processes and design new compounds of pharmaceutical interest. However, currently available tools for large-scale ligand identification fail to address many of the more complex ways in which ligands are stored and represented in PDB structures. Therefore, a new tool called LigExtract was specifically developed for the large-scale processing of PDB structures and the identification of their ligands. This is a fully open-source tool available to the scientific community, designed to provide end-to-end processing. Users simply provide a list of UniProt IDs, and LigExtract returns a list of ligands, their individual PDB files, a PDB file of the protein chains interacting with the ligand, and a series of log files. These logs record the decisions made during the ligand extraction process and flag additional scenarios that might have to be considered during any follow-up use of the processed files (e.g., ligands covalently bound to the protein). LigExtract is freely available on GitHub (https://github.com/comp-medchem/LigExtract).
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,850
OpenAlex ID: W4408141120