Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

MSDmotif: exploring protein sites and motifs

<p>Abstract</p> <p>Background</p> <p>Protein structures have conserved features – motifs, which have a sufficient influence on the protein function. These motifs can be found in sequence as well as in 3D space. Understanding of these fragments is essential for 3D structure prediction, modelling and drug-design. The Protein Data Bank (PDB) is the source of this information however present search tools have limited 3D options to integrate protein sequence with its 3D structure.</p> <p>Results</p> <p>We describe here a web application for querying the PDB for ligands, binding sites, small 3D structural and sequence motifs and the underlying database. Novel algorithms for chemical fragments, 3D motifs, ϕ/ψ sequences, super-secondary structure motifs and for small 3D structural motif associations searches are incorporated. The interface provides functionality for visualization, search criteria creation, sequence and 3D multiple alignment options. MSDmotif is an integrated system where a results page is also a search form. A set of motif statistics is available for analysis. This set includes molecule and motif binding statistics, distribution of motif sequences, occurrence of an amino-acid within a motif, correlation of amino-acids side-chain charges within a motif and Ramachandran plots for each residue. The binding statistics are presented in association with properties that include a ligand fragment library. Access is also provided through the distributed Annotation System (DAS) protocol. An additional entry point facilitates XML requests with XML responses.</p> <p>Conclusion</p> <p>MSDmotif is unique by combining chemical, sequence and 3D data in a single search engine with a range of search and visualisation options. It provides multiple views of data found in the PDB archive for exploring protein structures.</p

PDBe: Protein Data Bank in Europe

The Protein Data Bank in Europe (PDBe) (http://www.ebi.ac.uk/pdbe/) is actively working with its Worldwide Protein Data Bank partners to enhance the quality and consistency of the international archive of bio-macromolecular structure data, the Protein Data Bank (PDB). PDBe also works closely with its collaborators at the European Bioinformatics Institute and the scientific community around the world to enhance its databases and services by adding curated and actively maintained derived data to the existing structural data in the PDB. We have developed a new database infrastructure based on the remediated PDB archive data and a specially designed database for storing information on interactions between proteins and bound molecules. The group has developed new services that allow users to carry out simple textual queries or more complex 3D structure-based queries. The newly designed ‘PDBeView Atlas pages’ provide an overview of an individual PDB entry in a user-friendly layout and serve as a starting point to further explore the information available in the PDBe database. PDBe’s active involvement with the X-ray crystallography, Nuclear Magnetic Resonance spectroscopy and cryo-Electron Microscopy communities have resulted in improved tools for structure deposition and analysis

From protein sequences to 3D-structures and beyond: the example of the UniProt Knowledgebase

With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website (http://www.uniprot.org/). It also evokes precautions that are necessary for successful predictions and extrapolations

E-MSD: the European Bioinformatics Institute Macromolecular Structure Database

The E-MSD macromolecular structure relational database (http://www.ebi.ac.uk/msd) is designed to be a single access point for protein and nucleic acid structures and related information. The database is derived from Protein Data Bank (PDB) entries. Relational database technologies are used in a comprehensive cleaning procedure to ensure data uniformity across the whole archive. The search database contains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and PROSITE. A generic search interface is available, coupled with a fast secondary structure domain search tool

Crystal structure and mechanism of a bacterial fluorinating enzyme

Fluorine is the thirteenth most abundant element in the earth's crust, but fluoride concentrations in surface water are low and fluorinated metabolites are extremely rare. The fluoride ion is a potent nucleophile in its desolvated state, but is tightly hydrated in water and effectively inert. Low availability and a lack of chemical reactivity have largely excluded fluoride from biochemistry: in particular, fluorine's high redox potential precludes the haloperoxidase-type mechanism used in the metabolic incorporation of chloride and bromide ions. But fluorinated chemicals are growing in industrial importance, with applications in pharmaceuticals, agrochemicals and materials products. Reactive fluorination reagents requiring specialist process technologies are needed in industry and, although biological catalysts for these processes are highly sought after, only one enzyme that can convert fluoride to organic fluorine has been described. Streptomyces cattleya can form carbon-fluorine bonds and must therefore have evolved an enzyme able to overcome the chemical challenges of using aqueous fluoride. Here we report the sequence and three-dimensional structure of the first native fluorination enzyme, 5'-fluoro-5'-deoxyadenosine synthase, from this organism. Both substrate and products have been observed bound to the enzyme, enabling us to propose a nucleophilic substitution mechanism for this biological fluorination reaction

E-MSD: an integrated data resource for bioinformatics

The Macromolecular Structure Database (MSD) group (http://www.ebi.ac.uk/msd/) continues to enhance the quality and consistency of macromolecular structure data in the Protein Data Bank (PDB) and to work towards the integration of various bioinformatics data resources. We have implemented a simple form-based interface that allows users to query the MSD directly. The MSD ‘atlas pages’ show all of the information in the MSD for a particular PDB entry. The group has designed new search interfaces aimed at specific areas of interest, such as the environment of ligands and the secondary structures of proteins. We have also implemented a novel search interface that begins to integrate separate MSD search services in a single graphical tool. We have worked closely with collaborators to build a new visualization tool that can present both structure and sequence data in a unified interface, and this data viewer is now used throughout the MSD services for the visualization and presentation of search results. Examples showcasing the functionality and power of these tools are available from tutorial webpages (http://www.ebi.ac.uk/msd-srv/docs/roadshow_tutorial/)