A comparative view at comprehensive information resources on three-dimensional structures of biological macro-molecules.

The rapidly increasing amount of information on three-dimensional (3D) structures of biological macro-molecules has still an insufficient impact on genome analysis, functional genomics and proteomics as well as on many other fields in biomedicine including disease-related research. There are, however, attempts to make structural data more easily accessible to the bench biologist. As members of the world-wide Protein Data Bank (wwPDB), the RCSB Protein Data Bank (PDB), the Protein Data Bank Japan and the Macromolecular Structure Database are the primary information resources for 3D structures of proteins, nucleic acids, carbohydrates and complexes thereof. In addition, a number of secondary resources have been set up that also provide information on all currently known structures in a relatively comprehensive manner and not focusing on specific features only. They include PDBsum, the OCA browser-database for protein structure/function, the Molecular Modeling Database and the Jena Library of Biological Macromolecules--JenaLib. Both the primary and secondary resources often merge the information in the PDB files with data from other resources and offer additional analysis tools thereby adding value to the original PDB data. Here, we briefly describe these resources from a user's point of view and from a comparative perspective. It is our aim to guide researchers outside the structure biology field in getting the most out of the 3D structure resources.     

BioMagResBank (BMRB) as a partner in the Worldwide Protein Data Bank (wwPDB): new policies affecting biomolecular NMR depositions

We describe the role of the BioMagResBank (BMRB) within the Worldwide Protein Data Bank (wwPDB) and recent policies affecting the deposition of biomolecular NMR data. All PDB depositions of structures based on NMR data must now be accompanied by experimental restraints. A scheme has been devised that allows depositors to specify a representative structure and to define residues within that structure found experimentally to be largely unstructured. The BMRB now accepts coordinate sets representing three-dimensional structural models based on experimental NMR data of molecules of biological interest that fall outside the guidelines of the Protein Data Bank (i.e., the molecule is a peptide with 23 or fewer residues, a polynucleotide with 3 or fewer residues, a polysaccharide with 3 or fewer sugar residues, or a natural product), provided that the coordinates are accompanied by representation of the covalent structure of the molecule (atom connectivity), assigned NMR chemical shifts, and the structural restraints used in generating model. The BMRB now contains an archive of NMR data for metabolites and other small molecules found in biological systems.     

Citing a Data Repository: A Case Study of the Protein Data Bank

The Protein Data Bank (PDB) is the worldwide repository of 3D structures of proteins, nucleic acids and complex assemblies. The PDB’s large corpus of data (> 100,000 structures) and related citations provide a well-organized and extensive test set for developing and understanding data citation and access metrics. In this paper, we present a systematic investigation of how authors cite PDB as a data repository. We describe a novel metric based on information cascade constructed by exploring the citation network to measure influence between competing works and apply that to analyze different data citation practices to PDB. Based on this new metric, we found that the original publication of RCSB PDB in the year 2000 continues to attract most citations though many follow-up updates were published. None of these follow-up publications by members of the wwPDB organization can compete with the original publication in terms of citations and influence. Meanwhile, authors increasingly choose to use URLs of PDB in the text instead of citing PDB papers, leading to disruption of the growth of the literature citations. A comparison of data usage statistics and paper citations shows that PDB Web access is highly correlated with URL mentions in the text. The results reveal the trend of how authors cite a biomedical data repository and may provide useful insight of how to measure the impact of a data repository.     

The Protein Data Bank: unifying the archive

The Protein Data Bank (PDB; http://www.pdb.org/) is the single worldwide archive of structural data of biological macromolecules. This paper describes the progress that has been made in validating all data in the PDB archive and in releasing a uniform archive for the community. We have now produced a collection of mmCIF data files for the PDB archive (ftp://beta.rcsb.org/pub/pdb/uniformity/data/mmCIF/). A utility application that converts the mmCIF data files to the PDB format (called CIFTr) has also been released to provide support for existing software.     

Pre-calculated protein structure alignments at the RCSB PDB website

SUMMARY: With the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user. Availability and Implementation: A web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.org CONTACT: andreas@sdsc.edu; pbourne@ucsd.edu.     

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.     

TargetDB: a target registration database for structural genomics projects

TargetDB is a centralized target registration database that includes protein target data from the NIH structural genomics centers and a number of international sites. TargetDB, which is hosted by the Protein Data Bank (RCSB PDB), provides status information on target sequences and tracks their progress through the various stages of protein production and structure determination. A simple search form permits queries based on contributing site, target ID, protein name, sequence, status and other data. The progress of individual targets or entire structural genomics projects may be tracked over time, and target data from all contributing centers may also be downloaded in the XML format. AVAILABILITY: TargetDB is available at http://targetdb.pdb.org/     

Improving the representation of peptide‐like inhibitor and antibiotic molecules in the Protein Data Bank

With the accumulation of a large number and variety of molecules in the Protein Data Bank (PDB) comes the need on occasion to review and improve their representation. The Worldwide PDB (wwPDB) partners have periodically updated various aspects of structural data representation to improve the integrity and consistency of the archive. The remediation effort described here was focused on improving the representation of peptide‐like inhibitor and antibiotic molecules so that they can be easily identified and analyzed. Peptide‐like inhibitors or antibiotics were identified in over 1000 PDB entries, systematically reviewed and represented either as peptides with polymer sequence or as single components. For the majority of the single‐component molecules, their peptide‐like composition was captured in a new representation, called the subcomponent sequence. A novel concept called “group” was developed for representing complex peptide‐like antibiotics and inhibitors that are composed of multiple polymer and nonpolymer components. In addition, a reference dictionary was developed with detailed information about these peptide‐like molecules to aid in their annotation, identification and analysis. Based on the experience gained in this remediation, guidelines, procedures, and tools were developed to annotate new depositions containing peptide‐like inhibitors and antibiotics accurately and consistently. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 659–668, 2014.     

Vivaldi: Visualization and validation of biomacromolecular NMR structures from the PDB

We describe Vivaldi (VIsualization and VALidation DIsplay; http://pdbe.org/vivaldi ), a web‐based service for the analysis, visualization, and validation of NMR structures in the Protein Data Bank (PDB). Vivaldi provides access to model coordinates and several types of experimental NMR data using interactive visualization tools, augmented with structural annotations and model‐validation information. The service presents information about the modeled NMR ensemble, validation of experimental chemical shifts, residual dipolar couplings, distance and dihedral angle constraints, as well as validation scores based on empirical knowledge and databases. Vivaldi was designed for both expert NMR spectroscopists and casual non‐expert users who wish to obtain a better grasp of the information content and quality of NMR structures in the public archive. © Proteins 2013. © 2012 Wiley Periodicals, Inc.     

The PDB data uniformity project

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/) is the single worldwide archive of structural data of biological macromolecules. This paper describes the data uniformity project that is underway to address the inconsistency in PDB data.     

Homology‐based hydrogen bond information improves crystallographic structures in the PDB

The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H‐bond) distances as a source of information. However, H‐bond restraints can improve structures at low resolution where diffraction data are limited. To improve low‐resolution structure refinement, we present methods for deriving H‐bond information either globally from well‐refined high‐resolution structures from the PDB‐REDO databank, or specifically from on‐the‐fly constructed sets of homologous high‐resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low‐resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB‐REDO databank ( https://pdb-redo.eu ). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.     

The Protein Data Bank

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.     

Protein Circular Dichroism Data Bank (PCDDB): data bank and website design

The Protein Circular Dichroism Data Bank (PCDDB) is a new deposition data bank for validated circular dichroism spectra of biomacromolecules. Its aim is to be a resource for the structural biology and bioinformatics communities, providing open access and archiving facilities for circular dichroism and synchrotron radiation circular dichroism spectra. It is named in parallel with the Protein Data Bank (PDB), a long-existing valuable reference data bank for protein crystal and NMR structures. In this article, we discuss the design of the data bank structure and the deposition website located at http://pcddb.cryst.bbk.ac.uk. Our aim is to produce a flexible and comprehensive archive, which enables user-friendly spectral deposition and searching. In the case of a protein whose crystal structure and sequence are known, the PCDDB entry will be linked to the appropriate PDB and sequence data bank files, respectively. It is anticipated that the PCDDB will provide a readily accessible biophysical catalogue of information on folded proteins that may be of value in structural genomics programs, for quality control and archiving in industrial and academic labs, as a resource for programs developing spectroscopic structural analysis methods, and in bioinformatics studies.     

Protein Data Bank Japan: Celebrating our 20th anniversary during a global pandemic as the Asian hub of three dimensional macromolecular structural data

Protein Data Bank Japan (PDBj), a founding member of the worldwide Protein Data Bank (wwPDB) has accepted, processed and distributed experimentally determined biological macromolecular structures for 20 years. During that time, we have continuously made major improvements to our query search interface of PDBj Mine 2, the BMRBj web interface, and EM Navigator for PDB/BMRB/EMDB entries. PDBj also serves PDB‐related secondary database data, original web‐based modeling services such as Homology modeling of complex structure (HOMCOS), visualization services and utility tools, which we have continuously enhanced and expanded throughout the years. In addition, we have recently developed several unique archives, BSM‐Arc for computational structure models, and XRDa for raw X‐ray diffraction images, both of which promote open science in the structural biology community. During the COVID‐19 pandemic, PDBj has also started to provide feature pages for COVID‐19 related entries across all available archives at PDBj from raw experimental data and PDB structural data to computationally predicted models, while also providing COVID‐19 outreach content for high school students and teachers.     

Structural biology of G protein‐coupled receptor signaling complexes

G protein‐coupled receptors (GPCRs) constitute the largest family of cell surface receptors that mediate numerous cell signaling pathways, and are targets of more than one‐third of clinical drugs. Thanks to the advancement of novel structural biology technologies, high‐resolution structures of GPCRs in complex with their signaling transducers, including G‐protein and arrestin, have been determined. These 3D complex structures have significantly improved our understanding of the molecular mechanism of GPCR signaling and provided a structural basis for signaling‐biased drug discovery targeting GPCRs. Here we summarize structural studies of GPCR signaling complexes with G protein and arrestin using rhodopsin as a model system, and highlight the key features of GPCR conformational states in biased signaling including the sequence motifs of receptor TM6 that determine selective coupling of G proteins, and the phosphorylation codes of GPCRs for arrestin recruitment. We envision the future of GPCR structural biology not only to solve more high‐resolution complex structures but also to show stepwise GPCR signaling complex assembly and disassembly and dynamic process of GPCR signal transduction.     

Structural genomics is the largest contributor of novel structural leverage

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today’s UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849–851, 2007) has resulted from systematic targeting of large families. PSI’s per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another ~15 years to cover most sequences in the current UniProt database.     

The Protein Data Bank at 40: reflecting on the past to prepare for the future

A symposium celebrating the 40th anniversary of the Protein Data Bank archive (PDB), organized by the Worldwide Protein Data Bank, was held at Cold Spring Harbor Laboratory (CSHL) October 28-30, 2011. PDB40's distinguished speakers highlighted four decades of innovation in structural biology, from the early?era of structural determination to future directions for the field.     

Protein structure determination by conformational space annealing using NMR geometric restraints

We have carried out numerical experiments to investigate the applicability of the global optimization method of conformational space annealing (CSA) to the enhanced NMR protein structure determination over existing PDB structures. The NMR protein structure determination is driven by the optimization of collective multiple restraints arising from experimental data and the basic stereochemical properties of a protein‐like molecule. By rigorous and straightforward application of CSA to the identical NMR experimental data used to generate existing PDB structures, we redetermined 56 recent PDB protein structures starting from fully randomized structures. The quality of CSA‐generated structures and existing PDB structures were assessed by multiobjective functions in terms of their consistencies with experimental data and the requirements of protein‐like stereochemistry. In 54 out of 56 cases, CSA‐generated structures were better than existing PDB structures in the Pareto‐dominant manner, while in the remaining two cases, it was a tie with mixed results. As a whole, all structural features tested improved in a statistically meaningful manner. The most improved feature was the Ramachandran favored portion of backbone torsion angles with about 8.6% improvement from 88.9% to 97.5% (P‐value <10^?17). We show that by straightforward application of CSA to the efficient global optimization of an energy function, NMR structures will be of better quality than existing PDB structures. Proteins 2015; 83:2251–2262. © 2015 Wiley Periodicals, Inc.     

Population patch clamp electrophysiology: a breakthrough technology for ion channel screening

Population patch clamp (PPC) is a novel high throughput planar array electrophysiology technique that allows ionic currents to be recorded from populations of cells under voltage clamp. For the drug discovery pharmacologist, PPC promises greater speed and precision than existing methods for screening compounds at voltage-gated ion channel targets. Moreover, certain constitutively active or slow-ligand gated channels that have hitherto proved challenging to screen with planar array electrophysiology (e.g. SK/IK channels) are now more accessible. In this article we review early findings using PPC and provide a perspective on its likely impact on ion channel drug discovery. To support this, we include some new data on ion channel assay duplexing and on modulator assays, approaches that have thus far not been described.