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Acta Crystallogr D Biol Crystallogr. 2014 Jul;70(Pt 7):1844-53. doi: 10.1107/S1399004714008578. Epub 2014 Jun 29.

Automated identification of crystallographic ligands using sparse-density representations.

Author information

1
European Molecular Biology Laboratory (EMBL), c/o DESY, Notkestrasse 85, 22603 Hamburg, Germany.

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.

KEYWORDS:

drug design; ligands; macromolecular X-ray crystallography; shape descriptors

PMID:
25004962
PMCID:
PMC4089483
DOI:
10.1107/S1399004714008578
[Indexed for MEDLINE]
Free PMC Article

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