Automated protein-ligand crystallography for structure-based drug design.

An approach to automate protein-ligand crystallography is presented, with the aim of increasing the number of structures available to structure-based drug design. The methods we propose deal with the automatic interpretation of diffraction data for targets with known protein structures, and provide easy access to the results. Central to the system is a novel procedure that fully automates the placement of ligands into electron density maps. Automation provides an objective way to structure solution, whereas manual placement can be rather subjective, especially for data of low to medium resolution. Ligands are placed by docking into electron density, whilst taking care of protein-ligand interactions. The ligand fitting procedure has been validated on both public domain and in-house examples. Some of the latter deal with cocktails of low-molecular weight compounds, as used in fragment-based drug discovery by crystallography. For such library-screening experiments we show that the method can automatically identify which of the compounds from a cocktail is bound.