Validation of ligands in macromolecular structures determined by X‐ray crystallography. Issue 3 (5th April 2018)

• Record Type: Journal Article
• Authors: Smart, Oliver S.; Horský, Vladimír; Gore, Swanand; Svobodová Vařeková, Radka; Bendová, Veronika; Kleywegt, Gerard J.; Velankar, Sameer
• Is Part Of: Acta crystallographica. Volume 74:Issue 3(2018)
• Page Start: 228
• Page End: 236
• Publication Date: 2018-04-05
• Subjects: PDB -- Protein Data Bank -- three‐dimensional macromolecular structure -- validation -- ligands; X-ray crystallography -- Periodicals; Crystallography -- Periodicals; Molecular biology -- Periodicals; Molecular structure -- Periodicals; Biomolecules -- Structure -- Periodicals; Cytology -- Periodicals; Biomolecules -- Structure; Crystallography; Cytology; Molecular biology; Molecular structure; X-ray crystallography; Periodicals; 548
• DOI: 10.1107/S2059798318002541
• Languages: English
• ISSNs: 2059-7983

Abstract

Abstract : Better metrics are required to be able to assess small‐molecule ligands in macromolecular structures in Worldwide Protein Data Bank validation reports. The local ligand density fit (LLDF) score currently used to assess ligand electron‐density fit outliers produces a substantial number of false positives and false negatives. Abstract : Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) play a crucial role in structure‐guided drug discovery and design, and also provide atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. The quality with which small‐molecule ligands have been modelled in Protein Data Bank (PDB) entries has been, and continues to be, a matter of concern for many investigators. Correctly interpreting whether electron density found in a binding site is compatible with the soaked or co‐crystallized ligand or represents water or buffer molecules is often far from trivial. The Worldwide PDB validation report (VR) provides a mechanism to highlight any major issues concerning the quality of the data and the model at the time of deposition and annotation, so the depositors can fix issues, resulting in improved data quality. The ligand‐validation methods used in the generation of the current VRs are described in detail, including an examination of the metrics to assess both geometry and electron‐density fit. It is found that the LLDF score currently used to identify ligand electron‐density fit outliers can give misleading results and that better ligand‐validation metrics are required.