title: Automated identification of crystallographic ligands using sparse-density representations.
abstract: A novel procedure for the automatic identification of ligands in macromolecular crystallographic electron-density maps is introduced. It is based on the sparse parameterization of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. In large-scale tests on experimental data derived from the Protein Data Bank, the procedure could quickly identify the deposited ligand within the top-ranked compounds from a database of candidates. This indicates the suitability of the method for the identification of binding entities in fragment-based drug screening and in model completion in macromolecular structure determination.
authors.affiliation: European Molecular Biology Laboratory (EMBL), c/o DESY, Notkestrasse 85, 22603 Hamburg, Germany.
authors.forename: C G
authors.initials: CG
authors.lastname: Carolan
authors.affiliation: European Molecular Biology Laboratory (EMBL), c/o DESY, Notkestrasse 85, 22603 Hamburg, Germany.
authors.forename: V S
authors.initials: VS
authors.lastname: Lamzin
mesh_terms: D001331:Automation; D018360:Crystallography, X-Ray / Q000379:methods*; D030562:Databases, Protein; D008024:Ligands
chemical_list: D008024:Ligands
keywords: drug design; ligands; macromolecular X-ray crystallography; shape descriptors