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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.

SUBMITTER: Carolan CG

PROVIDER: S-EPMC4089483 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Automated identification of crystallographic ligands using sparse-density representations.

Carolan C G CG Lamzin V S VS

Acta crystallographica. Section D, Biological crystallography 20140629 Pt 7

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 with ...[more]

PMID: 25004962

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