Worldwide Protein Data Bank biocuration supporting open access to high-quality 3D structural biology data.

Database URL: https://www.wwpdb.org/.

Validation of Structures in the Protein Data Bank.

The Worldwide PDB recently launched a deposition, biocuration, and validation tool: OneDep. At various stages of OneDep data processing, validation reports for three-dimensional structures of biological macromolecules are produced. These reports are based on recommendations of expert task forces representing crystallography, nuclear magnetic resonance, and cryoelectron microscopy communities. The reports provide useful metrics with which depositors can evaluate the quality of the experimental data, the structural model, and the fit between them. The validation module is also available as a stand-alone web server and as a programmatically accessible web service. A growing number of journals require the official wwPDB validation reports (produced at biocuration) to accompany manuscripts describing macromolecular structures. Upon public release of the structure, the validation report becomes part of the public PDB archive. Geometric quality scores for proteins in the PDB archive have improved over the past decade.

OneDep: Unified wwPDB System for Deposition, Biocuration, and Validation of Macromolecular Structures in the PDB Archive.

OneDep, a unified system for deposition, biocuration, and validation of experimentally determined structures of biological macromolecules to the PDB archive, has been developed as a global collaboration by the worldwide PDB (wwPDB) partners. This new system was designed to ensure that the wwPDB could meet the evolving archiving requirements of the scientific community over the coming decades. OneDep unifies deposition, biocuration, and validation pipelines across all wwPDB, EMDB, and BMRB deposition sites with improved focus on data quality and completeness in these archives, while supporting growth in the number of depositions and increases in their average size and complexity. In this paper, we describe the design, functional operation, and supporting infrastructure of the OneDep system, and provide initial performance assessments.

PDBe: improved accessibility of macromolecular structure data from PDB and EMDB.

The Protein Data Bank in Europe (http://pdbe.org) accepts and annotates depositions of macromolecular structure data in the PDB and EMDB archives and enriches, integrates and disseminates structural information in a variety of ways. The PDBe website has been redesigned based on an analysis of user requirements, and now offers intuitive access to improved and value-added macromolecular structure information. Unique value-added information includes lists of reviews and research articles that cite or mention PDB entries as well as access to figures and legends from full-text open-access publications that describe PDB entries. A powerful new query system not only shows all the PDB entries that match a given query, but also shows the 'best structures' for a given macromolecule, ligand complex or sequence family using data-quality information from the wwPDB validation reports. A PDBe RESTful API has been developed to provide unified access to macromolecular structure data available in the PDB and EMDB archives as well as value-added annotations, e.g. regarding structure quality and up-to-date cross-reference information from the SIFTS resource. Taken together, these new developments facilitate unified access to macromolecular structure data in an intuitive way for non-expert users and support expert users in analysing macromolecular structure data.

PDBe: Protein Data Bank in Europe.

The Protein Data Bank in Europe (pdbe.org) is a founding member of the Worldwide PDB consortium (wwPDB; wwpdb.org) and as such is actively engaged in the deposition, annotation, remediation and dissemination of macromolecular structure data through the single global archive for such data, the PDB. Similarly, PDBe is a member of the EMDataBank organisation (emdatabank.org), which manages the EMDB archive for electron microscopy data. PDBe also develops tools that help the biomedical science community to make effective use of the data in the PDB and EMDB for their research. Here we describe new or improved services, including updated SIFTS mappings to other bioinformatics resources, a new browser for the PDB archive based on Gene Ontology (GO) annotation, updates to the analysis of Nuclear Magnetic Resonance-derived structures, redesigned search and browse interfaces, and new or updated visualisation and validation tools for EMDB entries.

The role of structural bioinformatics resources in the era of integrative structural biology.

The history and the current state of the PDB and EMDB archives is briefly described, as well as some of the challenges that they face. It seems natural that the role of structural biology archives will change from being a pure repository of historic data into becoming an indispensable resource for the wider biomedical community. As part of this transformation, it will be necessary to validate the biomacromolecular structure data and ensure the highest possible quality for the archive holdings, to combine structural data from different spatial scales into a unified resource and to integrate structural data with functional, genetic and taxonomic data as well as other information available in bioinformatics resources. Some recent developments and plans to address these challenges at PDBe are presented.

SIFTS: Structure Integration with Function, Taxonomy and Sequences resource.

The Structure Integration with Function, Taxonomy and Sequences resource (SIFTS; http://pdbe.org/sifts) is a close collaboration between the Protein Data Bank in Europe (PDBe) and UniProt. The two teams have developed a semi-automated process for maintaining up-to-date cross-reference information to UniProt entries, for all protein chains in the PDB entries present in the UniProt database. This process is carried out for every weekly PDB release and the information is stored in the SIFTS database. The SIFTS process includes cross-references to other biological resources such as Pfam, SCOP, CATH, GO, InterPro and the NCBI taxonomy database. The information is exported in XML format, one file for each PDB entry, and is made available by FTP. Many bioinformatics resources use SIFTS data to obtain cross-references between the PDB and other biological databases so as to provide their users with up-to-date information.

A Java applet for multiple linked visualization of protein structure and sequence.

The amount of biological data available from experimental techniques is huge, and rapidly expanding. The ability to make sense of this vast amount of data requires that we make correlations between distinct biological disciplines using visualization techniques to highlight the critical information. This article describes the visualization techniques of dynamic data brushing, view context maintenance, fisheye sequence view, and a magic lens that have been developed to display protein structure and sequence information.

Automated tracing of electron-density maps of proteins.

The tracing of experimental electron maps in the field of protein crystallography is not a rate-limiting step for structure elucidation, but does represent the process that requires the most expertise and user time. This paper presents a method for automatically tracing the electron-density maps of proteins which can reliably generate a C(alpha) trace for protein maps with data in the resolution range 1.5-4 A. The number of C(alpha) atoms placed and the precision of atom placement depends on the quality of the map, but even with poor maps (FOM approximately 0.5) the algorithm can provide a significant saving in time over conventional methods of interpretation. The interpretation of six experimental maps is presented at different resolutions and levels of phase error; these show that data with an FOM of 0.7 or better can be entirely traced with no user intervention.

High-resolution crystallographic map interpretation.

This article describes a method for rapid interpretation of high-resolution crystallographic electron-density maps. The implemented algorithm searches for fragments of structure found in proteins and links these together to identify uniquely the atomic structure and sequence order of the atoms within a protein. The algorithm uses a two-dimensional sub-graph isomorphism method with a subsequent post-processing step to screen the results to find correct three-dimensional solutions to each search fragment. The final screening of ambiguous solutions found is performed using incomplete difference distance matrices. The algorithm has an intrinsic error-correction technique that is necessary for analysis of experimental data and should be applicable to a number of fields of bioinfomatics.