Annotation and Curation of the Protein Data Bank

The Protein Data Bank (PDB) is the worldwide repository for experimentally determined 3D structures of biological macromolecules. Established in 1971 with just seven structures, it presently includes more than 56,000 entries. To maintain the highest standards in curation and processing, the members of the worldwide Protein Data Bank (wwPDB) collaborate in data annotation and the development of procedures, tools, and resources. Annotation-related issues, particularly those impacted by new developments
in structural biology, are critically reviewed at in-person and virtual meetings regularly and frequently. Comprehensive documentation of the procedures, formats, and related data dictionaries used in data annotation are available at the wwPDB website(www.wwpdb.org).

Mindful of the impact that changes in annotation procedures or data format may have on users, changes are carefully managed and communicated in a timely fashion. In cases involving complex scientific or policy issues, input is sought from advisory committees, standing task forces, experimental method developers, and community experts. This is exemplified by creation of the recently-released version of the PDB archive which updates and further standardizes database references, small molecule chemistry, biological assemblies, and active sites

Using structural analysis In Silico to assess the impact of missense variants in MEN1

Despite the rapid expansion in recent years of databases reporting either benign or pathogenic genetic variations, the interpretation of novel missense variants remains challenging, particularly for clinical or genetic testing laboratories where functional analysis is often unfeasible. Previous studies have shown that thermodynamic analysis of protein structure in silico can discriminate between groups of benign and pathogenic missense variants. However, although structures exist for many human disease‒associated proteins, such analysis remains largely unexploited in clinical laboratories. Here, we analyzed the predicted effect of 338 known missense variants on the structure of menin, the MEN1 gene product. Results provided strong discrimination between pathogenic and benign variants, with a threshold of >4 kcal/mol for the predicted change in stability, providing a strong indicator of pathogenicity. Subsequent analysis of seven novel missense variants identified during clinical testing of patients with MEN1 showed that all seven were predicted to destabilize menin by >4 kcal/mol. We conclude that structural analysis provides a useful tool in understanding the effect of missense variants in MEN1 and that integration of proteomic with genomic data could potentially contribute to the classification of novel variants in this disease.This article is freely available via Open Access. Click on the Publisher URL to access the full-text.Open Acces

The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries

Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483–186, 2004; Nederveen et al. in Proteins 59:662–672, 2005; Saccenti and Rosato in J Biomol NMR 40:251–261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376–384, 2009; Sanderson in Nature 459:1038–1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were ‘cleaned’ in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu

Outcome of the First wwPDB Hybrid / Integrative Methods Task Force Workshop

Structures of biomolecular systems are increasingly computed by integrative modeling that relies on varied types of experimental data and theoretical information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on October 6 and 7, 2014. At the workshop, experts in various experimental fields of structural biology, experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biology. How should integrative models be represented? How should the data and integrative models be validated? What data should be archived? How should the data and models be archived? What information should accompany the publication of integrative models

Nanobody structures

Many strategies have been developed to predict the function of amino acids and the effects of mutations. A multiple sequence alignment for a protein superfamily can be a powerful tool to transfer such information, but it also contains other relevant information about sequence variation and correlated mutations, for example. 3DM is a molecular-class-specific information system that creates an accurate structure-based multiple sequence alignment. Many derived data, such as correlated mutations, sequence variation, homology models, automatic mutation analyses, etc. are included. All of the information is stored in a relational database that revolves around a comprehensive 3D numbering scheme that encompasses all structurally equivalent positions, which allows the linking of all available data and the transfer of information between all sequences and structures. When building the 3DM for VHHs it was decided to not include the CDRs because their alignment is not reliably possible in an automated version. Consequently, homology models weren’t constructed and CDRs were not included in the alignments, correlated mutation calculations, but these topics are discussed in other chapters of this thesis