G. J. Swaminathan

PDBe: Protein Data Bank in Europe

The Protein Data Bank in Europe (PDBe; pdbe.org) is a partner in the Worldwide PDB organization (wwPDB; wwpdb.org) and as such actively involved in managing the single global archive of biomacromolecular structure data, the PDB. In addition, PDBe develops tools, services and resources to make structure-related data more accessible to the biomedical community. Here we describe recently developed, extended or improved services, including an animated structure-presentation widget (PDBportfolio), a widget to graphically display the coverage of any UniProt sequence in the PDB (UniPDB), chemistry- and taxonomy-based PDB-archive browsers (PDBeXplore), and a tool for interactive visualization of NMR structures, corresponding experimental data as well as validation and analysis results (Vivaldi).

The Matchmaker Exchange: a platform for rare disease gene discovery.

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for “the needle in a haystack” to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease‐specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can “match” these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

Structural Basis of Ordered Binding of Donor and Acceptor Substrates to the Retaining Glycosyltransferase, Alpha -1,3 Galactosyltransferase

Bovine α-1,3-galactosyltransferase (α3GT) catalyzes the synthesis of the α-galactose (α-Gal) epitope, the target of natural human antibodies. It represents a family of enzymes, including the histo blood group A and B transferases, that catalyze retaining glycosyltransfer reactions of unknown mechanism. An initial study of α3GT in a crystal form with limited resolution and considerable disorder suggested the possible formation of a β-galactosyl-enzyme covalent intermediate (Gastinel, L. N., Bignon, C., Misra, A. K., Hindsgaul, O., Shaper, J. H., and Joziasse, D. H. (2001) EMBO J. 20, 638–649). Highly ordered structures are described for complexes of α3GT with donor substrate, UDP-galactose, UDP- glucose, and two acceptor substrates, lactose and N-acetyllactosamine, at resolutions up to 1.46 Å. Structural and calorimetric binding studies suggest an obligatory ordered binding of donor and acceptor substrates, linked to a donor substrate-induced conformational change, and the direct participation of UDP in acceptor binding. The monosaccharide-UDP bond is cleaved in the structures containing UDP-galactose and UDP-glucose, producing non-covalent complexes containing buried β-galactose and α-glucose. The location of these monosaccharides and molecular modeling suggest that binding of a distorted conformation of UDP-galactose may be important in the catalytic mechanism of α3GT.

Data Deposition and Annotation at the Worldwide Protein Data Bank

The Protein Data Bank (PDB) is the repository for three-dimensional structures of biological macromolecules, determined by experimental methods. The data in the archive is free and easily available via the Internet from any of the worldwide centers managing this global archive. These data are used by scientists, researchers, bioinformatics specialists, educators, students, and general audiences to understand biological phenomenon at a molecular level. Analysis of this structural data also inspires and facilitates new discoveries in science. This chapter describes the tools and methods currently used for deposition, processing, and release of data in the PDB. References to future enhancements are also included.

The Crystal Structure of Human Placenta Growth Factor-1 (PlGF-1), an Angiogenic Protein, at 2.0 Å Resolution

The angiogenic molecule placenta growth factor (PlGF) is a member of the cysteine-knot family of growth factors. In this study, a mature isoform of the human PlGF protein, PlGF-1, was crystallized as a homodimer in the crystallographic asymmetric unit, and its crystal structure was elucidated at 2.0 Å resolution. The overall structure of PlGF-1 is similar to that of vascular endothelial growth factor (VEGF) with which it shares 42% amino acid sequence identity. Based on structural and biochemical data, we have mapped several important residues on the PlGF-1 molecule that are involved in recognition of the fms-like tyrosine kinase receptor (Flt-1, also known as VEGFR-1). We propose a model for the association of PlGF-1 and Flt-1 domain 2 with precise shape complementarity, consider the relevance of this assembly for PlGF-1 signal transduction, and provide a structural basis for altered specificity of this molecule.

Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families.

Discovery of most autosomal recessive disease-associated genes has involved analysis of large, often consanguineous multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of new dominant causes of rare, genetically heterogeneous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios. Here we analyzed 4,125 families with diverse, rare and genetically heterogeneous developmental disorders and identified four new autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (selecting probands with rare, biallelic and putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population and (ii) the phenotypic similarity of patients with recessive variants in the same candidate gene. This new paradigm promises to catalyze the discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations and those caused predominantly by compound heterozygous genotypes.

E-MSD: improving data deposition and structure quality

The Macromolecular Structure Database (MSD) () [H. Boutselakis, D. Dimitropoulos, J. Fillon, A. Golovin, K. Henrick, A. Hussain, J. Ionides, M. John, P. A. Keller, E. Krissinel et al. (2003) E-MSD: the European Bioinformatics Institute Macromolecular Structure Database. Nucleic Acids Res., 31, 458–462.] group is one of the three partners in the worldwide Protein DataBank (wwPDB), the consortium entrusted with the collation, maintenance and distribution of the global repository of macromolecular structure data [H. Berman, K. Henrick and H. Nakamura (2003) Announcing the worldwide Protein Data Bank. Nature Struct. Biol., 10, 980.]. Since its inception, the MSD group has worked with partners around the world to improve the quality of PDB data, through a clean up programme that addresses inconsistencies and inaccuracies in the legacy archive. The improvements in data quality in the legacy archive have been achieved largely through the creation of a unified data archive, in the form of a relational database that stores all of the data in the wwPDB. The three partners are working towards improving the tools and methods for the deposition of new data by the community at large. The implementation of the MSD database, together with the parallel development of improved tools and methodologies for data harvesting, validation and archival, has lead to significant improvements in the quality of data that enters the archive. Through this and related projects in the NMR and EM realms the MSD continues to improve the quality of publicly available structural data.

Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER

DECIPHER (https://decipher.sanger.ac.uk) is a web‐based platform for secure deposition, analysis, and sharing of plausibly pathogenic genomic variants from well‐phenotyped patients suffering from genetic disorders. DECIPHER aids clinical interpretation of these rare sequence and copy‐number variants by providing tools for variant analysis and identification of other patients exhibiting similar genotype–phenotype characteristics. DECIPHER also provides mechanisms to encourage collaboration among a global community of clinical centers and researchers, as well as exchange of information between clinicians and researchers within a consortium, to accelerate discovery and diagnosis. DECIPHER has contributed to matchmaking efforts by enabling the global clinical genetics community to identify many previously undiagnosed syndromes and new disease genes, and has facilitated the publication of over 700 peer‐reviewed scientific publications since 2004. At the time of writing, DECIPHER contains anonymized data from ∼250 registered centers on more than 51,500 patients (∼18000 patients with consent for data sharing and ∼25000 anonymized records shared privately). In this paper, we describe salient features of the platform, with special emphasis on the tools and processes that aid interpretation, sharing, and effective matchmaking with other data held in the database and that make DECIPHER an invaluable clinical and research resource.

Data deposition and annotation at the worldwide protein data bank.

The Protein Data Bank (PDB) is the repository for the three-dimensional structures of biological macromolecules, determined by experimental methods. The data in the archive are free and easily available via the Internet from any of the worldwide centers managing this global archive. These data are used by scientists, researchers, bioinformatics specialists, educators, students, and lay audiences to understand biological phenomena at a molecular level. Analysis of these structural data also inspires and facilitates new discoveries in science. This chapter describes the tools and methods currently used for deposition, processing, and release of data in the PDB. References to future enhancements are also included.