BioJava 5: A community driven open-source bioinformatics library.

BioJava is an open-source project that provides a Java library for processing biological data. The project aims to simplify bioinformatic analyses by implementing parsers, data structures, and algorithms for common tasks in genomics, structural biology, ontologies, phylogenetics, and more. Since 2012, we have released two major versions of the library (4 and 5) that include many new features to tackle challenges with increasingly complex macromolecular structure data. BioJava requires Java 8 or higher and is freely available under the LGPL 2.1 license. The project is hosted on GitHub at https://github.com/biojava/biojava. More information and documentation can be found online on the BioJava website (http://www.biojava.org) and tutorial (https://github.com/biojava/biojava-tutorial). All inquiries should be directed to the GitHub page or the BioJava mailing list (http://lists.open-bio.org/mailman/listinfo/biojava-l).

RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, rcsb.org), the US data center for the global PDB archive, serves thousands of Data Depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without usage restrictions to more than 1 million rcsb.org Users worldwide and 600 000 pdb101.rcsb.org education-focused Users around the globe. PDB Data Depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy and 3D electron microscopy. PDB Data Consumers include researchers, educators and students studying Fundamental Biology, Biomedicine, Biotechnology and Energy. Recent reorganization of RCSB PDB activities into four integrated, interdependent services is described in detail, together with tools and resources added over the past 2 years to RCSB PDB web portals in support of a 'Structural View of Biology.'

NGL viewer: web-based molecular graphics for large complexes.

Motivation: The interactive visualization of very large macromolecular complexes on the web is becoming a challenging problem as experimental techniques advance at an unprecedented rate and deliver structures of increasing size. Results: We have tackled this problem by developing highly memory-efficient and scalable extensions for the NGL WebGL-based molecular viewer and by using Macromolecular Transmission Format (MMTF), a binary and compressed MMTF. These enable NGL to download and render molecular complexes with millions of atoms interactively on desktop computers and smartphones alike, making it a tool of choice for web-based molecular visualization in research and education. Availability and implementation: The source code is freely available under the MIT license at github.com/arose/ngl and distributed on NPM (npmjs.com/package/ngl). MMTF-JavaScript encoders and decoders are available at github.com/rcsb/mmtf-javascript.

To what extent do structural changes in catalytic metal sites affect enzyme function?

About half of known enzymatic reactions involve metals. Enzymes belonging to the same superfamily often evolve to catalyze different reactions on the same structural scaffold. The work presented here investigates how functional differentiation, within superfamilies that contain metalloenzymes, relates to structural changes at the catalytic metal site. In general, when the catalytic metal site is unchanged across the enzymes of a superfamily, the functional differentiation within the superfamily tends to be low and the mechanism conserved. Conversely, all types of structural changes in the metal binding site are observed for superfamilies with high functional differentiation. Overall, the catalytic role of the metal ions appears to be one of the most conserved features of the enzyme mechanism within metalloenzyme superfamilies. In particular, when the catalytic role of the metal ion does not involve a redox reaction (i.e. there is no exchange of electrons with the substrate), this role is almost always maintained even when the site undergoes significant structural changes. In these enzymes, functional diversification is most often associated with modifications in the surrounding protein matrix, which has changed so much that the enzyme chemistry is significantly altered. On the other hand, in more than 50% of the examples where the metal has a redox role in catalysis, changes at the metal site modify its catalytic role. Further, we find that there are no examples in our dataset where metal sites with a redox role are lost during evolution. SYNOPSIS: In this paper we investigate how functional diversity within superfamilies of metalloenzymes relates to structural changes at the catalytic metal site. Evolution tends to strictly conserve the metal site. When changes occur, they do not modify the catalytic role of non-redox metals whereas they affect the role of redox-active metals.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework.

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

MMTF-An efficient file format for the transmission, visualization, and analysis of macromolecular structures.

Recent advances in experimental techniques have led to a rapid growth in complexity, size, and number of macromolecular structures that are made available through the Protein Data Bank. This creates a challenge for macromolecular visualization and analysis. Macromolecular structure files, such as PDB or PDBx/mmCIF files can be slow to transfer, parse, and hard to incorporate into third-party software tools. Here, we present a new binary and compressed data representation, the MacroMolecular Transmission Format, MMTF, as well as software implementations in several languages that have been developed around it, which address these issues. We describe the new format and its APIs and demonstrate that it is several times faster to parse, and about a quarter of the file size of the current standard format, PDBx/mmCIF. As a consequence of the new data representation, it is now possible to visualize structures with millions of atoms in a web browser, keep the whole PDB archive in memory or parse it within few minutes on average computers, which opens up a new way of thinking how to design and implement efficient algorithms in structural bioinformatics. The PDB archive is available in MMTF file format through web services and data that are updated on a weekly basis.

Towards an efficient compression of 3D coordinates of macromolecular structures.

The size and complexity of 3D macromolecular structures available in the Protein Data Bank is constantly growing. Current tools and file formats have reached limits of scalability. New compression approaches are required to support the visualization of large molecular complexes and enable new and scalable means for data analysis. We evaluated a series of compression techniques for coordinates of 3D macromolecular structures and identified the best performing approaches. By balancing compression efficiency in terms of the decompression speed and compression ratio, and code complexity, our results provide the foundation for a novel standard to represent macromolecular coordinates in a compact and useful file format.

The RCSB protein data bank: integrative view of protein, gene and 3D structural information.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a 'Structural View of Biology.' Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.

MetalPredator: a web server to predict iron-sulfur cluster binding proteomes.

MOTIVATION: The prediction of the iron-sulfur proteome is highly desirable for biomedical and biological research but a freely available tool to predict iron-sulfur proteins has not been developed yet. RESULTS: We developed a web server to predict iron-sulfur proteins from protein sequence(s). This tool, called MetalPredator, is able to process complete proteomes rapidly with high recall and precision. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at: http://metalweb.cerm.unifi.it/tools/metalpredator/ CONTACT: andreini@cerm.unifi.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Minimal Functional Sites in Metalloproteins and Their Usage in Structural Bioinformatics.

Metal ions play a functional role in numerous biochemical processes and cellular pathways. Indeed, about 40% of all enzymes of known 3D structure require a metal ion to be able to perform catalysis. The interactions of the metals with the macromolecular framework determine their chemical properties and reactivity. The relevant interactions involve both the coordination sphere of the metal ion and the more distant interactions of the so-called second sphere, i.e., the non-bonded interactions between the macromolecule and the residues coordinating the metal (metal ligands). The metal ligands and the residues in their close spatial proximity define what we call a minimal functional site (MFS). MFSs can be automatically extracted from the 3D structures of metal-binding biological macromolecules deposited in the Protein Data Bank (PDB). They are 3D templates that describe the local environment around a metal ion or metal cofactor and do not depend on the overall macromolecular structure. MFSs provide a different view on metal-binding proteins and nucleic acids, completely focused on the metal. Here we present different protocols and tools based upon the concept of MFS to obtain deeper insight into the structural and functional properties of metal-binding macromolecules. We also show that structure conservation of MFSs in metalloproteins relates to local sequence similarity more strongly than to overall protein similarity.

Hidden relationships between metalloproteins unveiled by structural comparison of their metal sites.

Metalloproteins account for a substantial fraction of all proteins. They incorporate metal atoms, which are required for their structure and/or function. Here we describe a new computational protocol to systematically compare and classify metal-binding sites on the basis of their structural similarity. These sites are extracted from the MetalPDB database of minimal functional sites (MFSs) in metal-binding biological macromolecules. Structural similarity is measured by the scoring function of the available MetalS2 program. Hierarchical clustering was used to organize MFSs into clusters, for each of which a representative MFS was identified. The comparison of all representative MFSs provided a thorough structure-based classification of the sites analyzed. As examples, the application of the proposed computational protocol to all heme-binding proteins and zinc-binding proteins of known structure highlighted the existence of structural subtypes, validated known evolutionary links and shed new light on the occurrence of similar sites in systems at different evolutionary distances. The present approach thus makes available an innovative viewpoint on metalloproteins, where the functionally crucial metal sites effectively lead the discovery of structural and functional relationships in a largely protein-independent manner.

MetalS(3), a database-mining tool for the identification of structurally similar metal sites.

We have developed a database search tool to identify metal sites having structural similarity to a query metal site structure within the MetalPDB database of minimal functional sites (MFSs) contained in metal-binding biological macromolecules. MFSs describe the local environment around the metal(s) independently of the larger context of the macromolecular structure. Such a local environment has a determinant role in tuning the chemical reactivity of the metal, ultimately contributing to the functional properties of the whole system. The database search tool, which we called MetalS(3) (Metal Sites Similarity Search), can be accessed through a Web interface at http://metalweb.cerm.unifi.it/tools/metals3/ . MetalS(3) uses a suitably adapted version of an algorithm that we previously developed to systematically compare the structure of the query metal site with each MFS in MetalPDB. For each MFS, the best superposition is kept. All these superpositions are then ranked according to the MetalS(3) scoring function and are presented to the user in tabular form. The user can interact with the output Web page to visualize the structural alignment or the sequence alignment derived from it. Options to filter the results are available. Test calculations show that the MetalS(3) output correlates well with expectations from protein homology considerations. Furthermore, we describe some usage scenarios that highlight the usefulness of MetalS(3) to obtain mechanistic and functional hints regardless of homology.

MetalS2: a tool for the structural alignment of minimal functional sites in metal-binding proteins and nucleic acids.

We developed a new software tool, MetalS(2), for the structural alignment of Minimal Functional Sites (MFSs) in metal-binding biological macromolecules. MFSs are 3D templates that describe the local environment around the metal(s) independently of the larger context of the macromolecular structure. Such local environment has a determinant role in tuning the chemical reactivity of the metal, ultimately contributing to the functional properties of the whole system. On our example data sets, MetalS(2) unveiled structural similarities that other programs for protein structure comparison do not consistently point out and overall identified a larger number of structurally similar MFSs. MetalS(2) supports the comparison of MFSs harboring different metals and/or with different nuclearity and is available both as a stand-alone program and a Web tool ( http://metalweb.cerm.unifi.it/tools/metals2/).