Abstract
SummaryStructures in PDB tend to contain errors. This is a very serious issue for authors that rely on such potentially problematic data. The community of structural biologists develops validation methods as countermeasures, which are also included in the PDB deposition system. But how are these validation efforts influencing the structure quality of subsequently published data? Which quality aspects are improving, and which remain problematic? We developed ValTrendsDB, a database that provides the results of an extensive exploratory analysis of relationships between quality criteria, size and metadata of biomacromolecules. Key input data are sourced from PDB. The discovered trends are presented via precomputed information-rich plots. ValTrendsDB also supports the visualization of a set of user-defined structures on top of general quality trends. Therefore, ValTrendsDB enables users to see the quality of structures published by selected author, laboratory or journal, discover quality outliers, etc. ValTrendsDB is updated weekly.Availability and implementationFreely accessible at http://ncbr.muni.cz/ValTrendsDB. The web interface was implemented in JavaScript. The database was implemented in C++.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Biomacromolecular structural data are key results of modern life sciences
The community of structural biologists develops validation methods as countermeasures, which are included in the Protein Data Bank (PDB) deposition system
How are these validation efforts influencing the structure quality of subsequently published data? Which quality aspects are improving, and which remain problematic? We developed ValTrendsDB, a database that provides the results of an extensive exploratory analysis of relationships between quality criteria, size and metadata of biomacromolecules
Summary
Biomacromolecular structural data are key results of modern life sciences. Most structures of biomacromolecules and their ligands are accessible via the Protein Data Bank (PDB) database (Burley et al, 2018). Some structures were found to contain serious errors (Rupp, 2012) This discovery showed the importance of the validation of biomacromolecular complexes. The first validation approaches were focused on the geometric properties of standard biomacromolecular residues (i.e. amino acids, nucleotides) (Chen et al, 2010). This validation approach was later extended to validate ligands (Bruno et al, 2004). Our cooperation with the Protein Data Bank in Europe (PDBe) motivated us to ask broader questions: How is the quality of biomacromolecular complexes changing over time? Its results can be explored in the novel ValTrendsDB database
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