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

Protein structure annotation resources

A key reason three-dimensional (3-D) protein structures are annotated with supporting or derived information is to understand the molecular basis of protein function. To this end, protein structure annotation databases curate key facts and observations, based on community-accepted standards, about the ~100,000 3-D experimental protein structures to date. This review will introduce the primary structure repositories, databases, and value-added structural annotation databases, as well as the range of information they provide. The different levels of annotation data (primary vs. derived vs. inferred) and how they should all be considered accordingly will also be described.

Protein structural information derived from NMR chemical shift with the neural network program TALOS-N

Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trained to extract backbone and side-chain torsion angles from (1)H, (15)N, and (13)C shifts. The program is quite robust and typically yields backbone torsion angles for more than 90 % of the residues and side-chain χ 1 rotamer information for about half of these, in addition to reliably predicting secondary structure. The use of TALOS-N is illustrated for the protein DinI, and torsion angles obtained by TALOS-N analysis from the measured chemical shifts of its backbone and (13)C(β) nuclei are compared to those seen in a prior, experimentally determined structure. The program is also particularly useful for generating torsion angle restraints, which then can be used during standard NMR protein structure calculations.

The chemical component dictionary: complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank

The Chemical Component Dictionary (CCD) is a chemical reference data resource that describes all residue and small molecule components found in Protein Data Bank (PDB) entries. The CCD contains detailed chemical descriptions for standard and modified amino acids/nucleotides, small molecule ligands and solvent molecules. Each chemical definition includes descriptions of chemical properties such as stereochemical assignments, chemical descriptors, systematic chemical names and idealized coordinates. The content, preparation, validation and distribution of this CCD chemical reference dataset are described.

AVAILABILITY AND IMPLEMENTATION

The CCD is updated regularly in conjunction with the scheduled weekly release of new PDB structure data. The CCD and amino acid variant reference datasets are hosted in the public PDB ftp repository at ftp://ftp.wwpdb.org/pub/pdb/data/monomers/components.cif.gz, ftp://ftp.wwpdb.org/pub/pdb/data/monomers/aa-variants-v1.cif.gz, and its mirror sites, and can be accessed from http://wwpdb.org.

CONTACT

jwest@rcsb.rutgers.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Protein Data Bank archive as an open data resource

The Protein Data Bank archive was established in 1971, and recently celebrated its 40th anniversary (Berman et al. in Structure 20:391, 2012). An analysis of interrelationships of the science, technology and community leads to further insights into how this resource evolved into one of the oldest and most widely used open-access data resources in biology.

Influence of iron and aeration on Staphylococcus aureus growth, metabolism, and transcription

Staphylococcus aureus is a prominent nosocomial pathogen and a major cause of biomaterial-associated infections. The success of S. aureus as a pathogen is due in part to its ability to adapt to stressful environments. As an example, the transition from residing in the nares to residing in the blood or deeper tissues is accompanied by changes in the availability of nutrients and elements such as oxygen and iron. As such, nutrients, oxygen, and iron are important determinants of virulence factor synthesis in S. aureus. In addition to influencing virulence factor synthesis, oxygen and iron are critical cofactors in enzymatic and electron transfer reactions; thus, a change in iron or oxygen availability alters the bacterial metabolome. Changes in metabolism create intracellular signals that alter the activity of metabolite-responsive regulators such as CodY, RpiRc, and CcpA. To assess the extent of metabolomic changes associated with oxygen and iron limitation, S. aureus cells were cultivated in iron-limited medium and/or with decreasing aeration, and the metabolomes were examined by nuclear magnetic resonance (NMR) spectroscopy. As expected, oxygen and iron limitation dramatically decreased tricarboxylic acid (TCA) cycle activity, creating a metabolic block and significantly altering the metabolome. These changes were most prominent during post-exponential-phase growth, when TCA cycle activity was maximal. Importantly, many of the effects of iron limitation were obscured by aeration limitation. Aeration limitation not only obscured the metabolic effects of iron limitation but also overrode the transcription of iron-regulated genes. Finally, in contrast to previous speculation, we confirmed that acidification of the culture medium occurs independent of the availability of iron.

Metabolic footprinting: extracellular metabolomic analysis

Uptake and excretion of nutrients is an integral part of a cell's physiology. Using analytical chemistry techniques, metabolite uptake and excretion from the culture medium can be quantified. As cellular metabolism changes throughout growth, additional information is available if transient and growth phase-dependent changes are monitored. Here, we describe time-resolved metabolic footprinting (TReF), a technique which employs nuclear magnetic resonance spectroscopy and nonlinear curve fitting to understand and visualize metabolite utilization of P. aeruginosa.

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

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.

High-resolution NMR reveals secondary structure and folding of amino acid transporter from outer chloroplast membrane

Solving high-resolution structures for membrane proteins continues to be a daunting challenge in the structural biology community. In this study we report our high-resolution NMR results for a transmembrane protein, outer envelope protein of molar mass 16 kDa (OEP16), an amino acid transporter from the outer membrane of chloroplasts. Three-dimensional, high-resolution NMR experiments on the ¹³C, ¹⁵N, ²H-triply-labeled protein were used to assign protein backbone resonances and to obtain secondary structure information. The results yield over 95% assignment of N, H_N, CO, C_α, and C_β chemical shifts, which is essential for obtaining a high resolution structure from NMR data. Chemical shift analysis from the assignment data reveals experimental evidence for the first time on the location of the secondary structure elements on a per residue basis. In addition T_1Z and T₂ relaxation experiments were performed in order to better understand the protein dynamics. Arginine titration experiments yield an insight into the amino acid residues responsible for protein transporter function. The results provide the necessary basis for high-resolution structural determination of this important plant membrane protein.

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (ϕ, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ(1) rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.

HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease

Effective diagnosis and surveillance of bladder cancer (BCa) is currently challenged by detection methods that are of poor sensitivity, particularly for low-grade tumors, resulting in unnecessary invasive procedures and economic burden. We performed HR-MAS NMR-based global metabolomic profiling and applied unsupervised principal component analysis (PCA) and hierarchical clustering performed on NMR data set of bladder-derived tissues and identified metabolic signatures that differentiate BCa from benign disease. A partial least-squares discriminant analysis (PLS-DA) model (leave-one-out cross-validation) was used as a diagnostic model to distinguish benign and BCa tissues. Receiver operating characteristic curve generated either from PC1 loadings of PCA or from predicted Y-values resulted in an area under curve of 0.97. Relative quantification of more than 15 tissue metabolites derived from HR-MAS NMR showed significant differences (P < 0.001) between benign and BCa samples. Noticeably, striking metabolic signatures were observed even for early stage BCa tissues (Ta-T1), demonstrating the sensitivity in detecting BCa. With the goal of cross-validating metabolic signatures derived from HR-MAS NMR, we utilized the same tissue samples to analyze 8 metabolites through gas chromatography-mass spectrometry (GC-MS)-targeted analysis, which undoubtedly complements HR-MAS NMR-derived metabolomic information. Cross-validation through GC-MS clearly demonstrates the utility of a straightforward, nondestructive, and rapid HR-MAS NMR technique for clinical diagnosis of BCa with even greater sensitivity. In addition to its utility as a diagnostic tool, these studies will lead to a better understanding of aberrant metabolic pathways in cancer as well as the design and implementation of personalized cancer therapy through metabolic modulation.

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of (13)C and (15)N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D (13)C-(13)C, (15)N-(13)C, or 3D (15)N-(13)C-(13)C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D (13)C-(13)C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40-60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO-Cα-Cβ or N-Cα-Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.

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.

Trendspotting in the Protein Data Bank

The Protein Data Bank (PDB) was established in 1971 as a repository for the three dimensional structures of biological macromolecules. Since then, more than 85000 biological macromolecule structures have been determined and made available in the PDB archive. Through analysis of the corpus of data, it is possible to identify trends that can be used to inform us abou the future of structural biology and to plan the best ways to improve the management of the ever-growing amount of PDB data.

Peakr: simulating solid-state NMR spectra of proteins

MOTIVATION

When analyzing solid-state nuclear magnetic resonance (NMR) spectra of proteins, assignment of resonances to nuclei and derivation of restraints for 3D structure calculations are challenging and time-consuming processes. Simulated spectra that have been calculated based on, for example, chemical shift predictions and structural models can be of considerable help. Existing solutions are typically limited in the type of experiment they can consider and difficult to adapt to different settings.

RESULTS

Here, we present Peakr, a software to simulate solid-state NMR spectra of proteins. It can generate simulated spectra based on numerous common types of internuclear correlations relevant for assignment and structure elucidation, can compare simulated and experimental spectra and produces lists and visualizations useful for analyzing measured spectra. Compared with other solutions, it is fast, versatile and user friendly.

AVAILABILITY AND IMPLEMENTATION

Peakr is maintained under the GPL license and can be accessed at http://www.peakr.org. The source code can be obtained on request from the authors.

Secondary structural analysis of proteins based on (13)C chemical shift assignments in unresolved solid-state NMR spectra enhanced by fragmented structure database

Magic-angle-spinning solid-state (13)C NMR spectroscopy is useful for structural analysis of non-crystalline proteins. However, the signal assignments and structural analysis are often hampered by the signal overlaps primarily due to minor structural heterogeneities, especially for uniformly-(13)C,(15)N labeled samples. To overcome this problem, we present a method for assigning (13)C chemical shifts and secondary structures from unresolved two-dimensional (13)C-(13)C MAS NMR spectra by spectral fitting, named reconstruction of spectra using protein local structures (RESPLS). The spectral fitting was conducted using databases of protein fragmented structures related to (13)C(α), (13)C(β), and (13)C' chemical shifts and cross-peak intensities. The experimental (13)C-(13)C inter- and intra-residue correlation spectra of uniformly isotope-labeled ubiquitin in the lyophilized state had a few broad peaks. The fitting analysis for these spectra provided sequence-specific C(α), C(β), and C' chemical shifts with an accuracy of about 1.5 ppm, which enabled the assignment of the secondary structures with an accuracy of 79 %. The structural heterogeneity of the lyophilized ubiquitin is revealed from the results. Test of RESPLS analysis for simulated spectra of five different types of proteins indicated that the method allowed the secondary structure determination with accuracy of about 80 % for the 50-200 residue proteins. These results demonstrate that the RESPLS approach expands the applicability of the NMR to non-crystalline proteins exhibiting unresolved (13)C NMR spectra, such as lyophilized proteins, amyloids, membrane proteins and proteins in living cells.

CING: an integrated residue-based structure validation program suite

We present a suite of programs, named CING for Common Interface for NMR Structure Generation that provides for a residue-based, integrated validation of the structural NMR ensemble in conjunction with the experimental restraints and other input data. External validation programs and new internal validation routines compare the NMR-derived models with empirical data, measured chemical shifts, distance- and dihedral restraints and the results are visualized in a dynamic Web 2.0 report. A red-orange-green score is used for residues and restraints to direct the user to those critiques that warrant further investigation. Overall green scores below ~20 % accompanied by red scores over ~50 % are strongly indicative of poorly modelled structures. The publically accessible, secure iCing webserver ( https://nmr.le.ac.uk ) allows individual users to upload the NMR data and run a CING validation analysis.

Creating a community resource for protein science

In addition to being one of the early pioneers in protein crystallography, Carl Brändén made significant contributions to science education with his elegant and beautifully illustrated book Introduction to Protein Structure (Brändén and Tooze, New York: Garland, 1991). It is truly an honor to receive this award in their names. This award and the 40th anniversary of the Protein Data Bank (PDB; Berman et al., Structure 2012;20:391-396) have given me an opportunity to reflect on the various components that have contributed to building a resource for protein science and to try to quantify the impact of having PDB data openly available.

PACSY, a relational database management system for protein structure and chemical shift analysis

PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.edu.

Changes in the metabolome and histopathology of Amaranthus hypochondriacus L. in response to Ageratum enation virus infection

Amaranthus hypochondriacus L. infected with Ageratum enation virus (AEV) was investigated for identifying alteration in the anatomical structures, sap translocation and metabolomic variations using light microscopy, magnetic resonance imaging, NMR spectroscopy and GC-MS, respectively. Combination of GC-MS and NMR spectroscopy identified 68 polar and non-polar metabolites that were present in different levels in healthy and virus-infected A. hypochondriacus. Contrast of T₁ and T₂ weighted MR images showed significant differences in the spatial distribution of water, lipids and macromolecules indicating alterations in the cortical region and disruption of vascular bundles in virus-infected stem tissues. MRI observations are supported by light microscopic examination. Microscopic examination of AEV infected stem revealed severe hyperplasia with a considerable reduction in size of stem cells. The NMR spectroscopy and GC-MS analysis indicated that viral infection significantly affected the plant primary and secondary metabolism resulting in decreased glucose and sucrose content and increase in the concentration of β-sitosterol and stigmasterol. Higher accumulation of TCA cycle intermediates such as citric acid and malic acid in AEV infected plants indicated enhanced rate of respiratory metabolism. The viral stress significantly increases the concentration of erythritol and myo-inositol as compared to healthy ones. Lower concentration of glucose and sucrose in viral-infected stem tissues suggests decreased translocation of photosynthates in the plants. The results demonstrated potential of MRI, NMR spectroscopy and GC-MS for studying anatomical and metabolic variations in virus-infected plants.

The UniProtKB/Swiss-Prot Tox-Prot program: A central hub of integrated venom protein data

Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

ECOMICS: a web-based toolkit for investigating the biomolecular web in ecosystems using a trans-omics approach

Ecosystems can be conceptually thought of as interconnected environmental and metabolic systems, in which small molecules to macro-molecules interact through diverse networks. State-of-the-art technologies in post-genomic science offer ways to inspect and analyze this biomolecular web using omics-based approaches. Exploring useful genes and enzymes, as well as biomass resources responsible for anabolism and catabolism within ecosystems will contribute to a better understanding of environmental functions and their application to biotechnology. Here we present ECOMICS, a suite of web-based tools for ECosystem trans-OMICS investigation that target metagenomic, metatranscriptomic, and meta-metabolomic systems, including biomacromolecular mixtures derived from biomass. ECOMICS is made of four integrated webtools. E-class allows for the sequence-based taxonomic classification of eukaryotic and prokaryotic ribosomal data and the functional classification of selected enzymes. FT2B allows for the digital processing of NMR spectra for downstream metabolic or chemical phenotyping. Bm-Char allows for statistical assignment of specific compounds found in lignocellulose-based biomass, and HetMap is a data matrix generator and correlation calculator that can be applied to trans-omics datasets as analyzed by these and other web tools. This web suite is unique in that it allows for the monitoring of biomass metabolism in a particular environment, i.e., from macromolecular complexes (FT2DB and Bm-Char) to microbial composition and degradation (E-class), and makes possible the understanding of relationships between molecular and microbial elements (HetMap). This website is available to the public domain at: https://database.riken.jp/ecomics/.

Dynamics of biomolecules from picoseconds to seconds at atomic resolution

Although biomolecular dynamics has been investigated using NMR for at least 40 years, only in the past 20 years have internal motions been characterized at atomic resolution throughout proteins and nucleic acids. This development was made possible by multidimensional heteronuclear NMR approaches that provide near complete sequential signal assignments of uniformly labeled biomolecules. Recent methodological advances have enabled characterization of internal dynamics on timescales ranging from picoseconds to seconds, both in solution and in the solid state. The size, complexity and functional significance of biomolecules investigated by NMR continue to grow, as do the insights that have been obtained about function. In this article I review a number of recent advances that have made such studies possible, and provide a few examples of where NMR either by itself or in combination with other approaches has paved the way to a better understanding of the complex relationship between dynamics and biomolecular function. Finally, I discuss prospects for further advances in this field.

Overview on the use of NMR to examine protein structure

Any protein structure determination process contains several steps, starting from obtaining a suitable sample, then moving on to acquiring data and spectral assignment, and lastly to the final steps of structure determination and validation. This unit describes all of these steps, starting with the basic physical principles behind NMR and some of the most commonly measured and observed phenomena such as chemical shift, scalar and residual coupling, and the nuclear Overhauser effect. Then, in somewhat more detail, the process of spectral assignment and structure elucidation is explained. Furthermore, the use of NMR to study protein-ligand interaction, protein dynamics, or protein folding is described.

Graphical representation and mathematical characterization of protein sequences and applications to viral proteins

Graphical representation and numerical characterization (GRANCH) of nucleotide and protein sequences is a new field that is showing a lot of promise in analysis of such sequences. While formulation and applications of GRANCH techniques for DNA/RNA sequences started just over a decade ago, analyses of protein sequences by these techniques are of more recent origin. The emphasis is still on developing the underlying technique, but significant results have been achieved in using these methods for protein phylogeny, mass spectral data of proteins and protein serum profiles in parasites, toxicoproteomics, determination of different indices for use in QSAR studies, among others. We briefly mention these in this chapter, with some details on protein phylogeny and viral diseases. In particular, we cover a systematic method developed in GRANCH to determine conserved surface exposed peptide segments in selected viral proteins that can be used for drug and vaccine targeting. The new GRANCH techniques and applications for DNAs and proteins are covered briefly to provide an overview to this nascent field.

Straightforward and complete deposition of NMR data to the PDBe

We present a suite of software for the complete and easy deposition of NMR data to the PDB and BMRB. This suite uses the CCPN framework and introduces a freely downloadable, graphical desktop application called CcpNmr Entry Completion Interface (ECI) for the secure editing of experimental information and associated datasets through the lifetime of an NMR project. CCPN projects can be created within the CcpNmr Analysis software or by importing existing NMR data files using the CcpNmr FormatConverter. After further data entry and checking with the ECI, the project can then be rapidly deposited to the PDBe using AutoDep, or exported as a complete deposition NMR-STAR file. In full CCPN projects created with ECI, it is straightforward to select chemical shift lists, restraint data sets, structural ensembles and all relevant associated experimental collection details, which all are or will become mandatory when depositing to the PDB. Instructions and download information for the ECI are available from the PDBe web site at http://www.ebi.ac.uk/pdbe/nmr/deposition/eci.html .

Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy

The study of biological systems in a holistic manner (systems biology) is increasingly being viewed as a necessity to provide qualitative and quantitative descriptions of the emergent properties of the complete system. Systems biology performs studies focussed on the complex interactions of system components; emphasising the whole system rather than the individual parts. Many perturbations to mammalian systems (diet, disease, drugs) are multi-factorial and the study of small parts of the system is insufficient to understand the complete phenotypic changes induced. Metabolomics is one functional level tool being employed to investigate the complex interactions of metabolites with other metabolites (metabolism) but also the regulatory role metabolites provide through interaction with genes, transcripts and proteins (e.g. allosteric regulation). Technological developments are the driving force behind advances in scientific knowledge. Recent advances in the two analytical platforms of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have driven forward the discipline of metabolomics. In this critical review, an introduction to metabolites, metabolomes, metabolomics and the role of MS and NMR spectroscopy will be provided. The applications of metabolomics in mammalian systems biology for the study of the health-disease continuum, drug efficacy and toxicity and dietary effects on mammalian health will be reviewed. The current limitations and future goals of metabolomics in systems biology will also be discussed (374 references).

NMR Constraints Analyser: a web-server for the graphical analysis of NMR experimental constraints

Nuclear magnetic resonance (NMR) spectroscopy together with X-ray crystallography, are the main techniques used for the determination of high-resolution 3D structures of biological molecules. The output of an NMR experiment includes a set of lower and upper limits for the distances (constraints) between pairs of atoms. If the number of constraints is high enough, there will be a finite number of possible conformations (models) of the macromolecule satisfying the data. Thus, the more constraints are measured, the better defined these structures will be. The availability of a user-friendly tool able to help in the analysis and interpretation of the number of experimental constraints per residue, is thus of valuable importance when assessing the levels of structure definition of NMR solved biological macromolecules, in particular, when high-quality structures are needed in techniques such as, computational biology approaches, site-directed mutagenesis experiments and/or drug design. Here, we present a free publicly available web-server, i.e. NMR Constraints Analyser, which is aimed at providing an automatic graphical analysis of the NMR experimental constraints atom by atom. The NMR Constraints Analyser server is available from the web-page http://molsim.sci.univr.it/constraint.

Prediction of Xaa-Pro peptide bond conformation from sequence and chemical shifts

We present a program, named Promega, to predict the Xaa-Pro peptide bond conformation on the basis of backbone chemical shifts and the amino acid sequence. Using a chemical shift database of proteins of known structure together with the PDB-extracted amino acid preference of cis Xaa-Pro peptide bonds, a cis/trans probability score is calculated from the backbone and (13)C(beta) chemical shifts of the proline and its neighboring residues. For an arbitrary number of input chemical shifts, which may include Pro-(13)C(gamma), Promega calculates the statistical probability that a Xaa-Pro peptide bond is cis. Besides its potential as a validation tool, Promega is particularly useful for studies of larger proteins where Pro-(13)C(gamma) assignments can be challenging, and for on-going efforts to determine protein structures exclusively on the basis of backbone and (13)C(beta) chemical shifts.

Animal Toxins: How is Complexity Represented in Databases?

Peptide toxins synthesized by venomous animals have been extensively studied in the last decades. To be useful to the scientific community, this knowledge has been stored, annotated and made easy to retrieve by several databases. The aim of this article is to present what type of information users can access from each database. ArachnoServer and ConoServer focus on spider toxins and cone snail toxins, respectively. UniProtKB, a generalist protein knowledgebase, has an animal toxin-dedicated annotation program that includes toxins from all venomous animals. Finally, the ATDB metadatabase compiles data and annotations from other databases and provides toxin ontology.

Cell-free protein synthesis technology in NMR high-throughput structure determination

This chapter describes the current implementation of the cell-free translation platform developed at the Center for Eukaryotic Structural Genomics (CESG) and practical aspects of the production of stable isotope-labeled eukaryotic proteins for NMR structure determination. Protocols are reported for the use of wheat germ cell-free translation in small-scale screening for the level of total protein expression, the solubility of the expressed protein, and the success in purification as predictive indicators of the likelihood that a protein may be obtained in sufficient quantity and quality to initiate structural studies. In most circumstances, the small-scale reactions also produce sufficient protein to permit bioanalytical and functional characterizations. The protocols incorporate the use of robots specialized for small-scale cell-free translation, large-scale protein production, and automated purification of soluble, His(6)-tagged proteins. The integration of isotopically labeled proteins into the sequence of experiments required for NMR structure determination is outlined, and additional protocols for production of integral membrane proteins in the presence of either detergents or unilamellar liposomes are presented.

DNP enhanced frequency-selective TEDOR experiments in bacteriorhodopsin

We describe a new approach to multiple (13)C-(15)N distance measurements in uniformly labeled solids, frequency-selective (FS) TEDOR. The method shares features with FS-REDOR and ZF- and BASE-TEDOR, which also provide quantitative (15)N-(13)C spectral assignments and distance measurements in U-[(13)C,(15)N] samples. To demonstrate the validity of the FS-TEDOR sequence, we measured distances in [U-(13)C,(15)N]-asparagine which are in good agreement with other methods. In addition, we integrate high frequency dynamic nuclear polarization (DNP) into the experimental protocol and use FS-TEDOR to record a resolved correlation spectrum of the Arg-(13)C(gamma)-(15)N(epsilon) region in [U-(13)C,(15)N]-bacteriorhodopsin. We resolve six of the seven cross-peaks expected based on the primary sequence of this membrane protein.

The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries

Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483-186, 2004; Nederveen et al. in Proteins 59:662-672, 2005; Saccenti and Rosato in J Biomol NMR 40:251-261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376-384, 2009; Sanderson in Nature 459:1038-1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were 'cleaned' in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu .

Structure, dynamics and mapping of membrane-binding residues of micelle-bound antimicrobial peptides by natural abundance (13)C NMR spectroscopy

Worldwide bacterial resistance to traditional antibiotics has drawn much research attention to naturally occurring antimicrobial peptides (AMPs) owing to their potential as alternative antimicrobials. Structural studies of AMPs are essential for an in-depth understanding of their activity, mechanism of action, and in guiding peptide design. Two-dimensional solution proton NMR spectroscopy has been the major tool. In this article, we describe the applications of natural abundance (13)C NMR spectroscopy that provides complementary information to 2D (1)H NMR. The correlation of (13)Calpha secondary shifts with both 3D structure and heteronuclear (15)N NOE values indicates that natural abundance carbon chemical shifts are useful probes for backbone structure and dynamics of membrane peptides. Using human LL-37-derived peptides (GF-17, KR-12, and RI-10), as well as amphibian antimicrobial and anticancer peptide aurein 1.2 and its analog LLAA, as models, we show that the cross peak intensity plots of 2D (1)H-(13)Calpha HSQC spectra versus residue number present a wave-like pattern (HSQC wave) where key hydrophobic residues of micelle-bound peptides are located in the troughs with weaker intensities, probably due to fast exchange between the free and bound forms. In all the cases, the identification of aromatic phenylalanines as a key membrane-binding residue is consistent with previous intermolecular Phe-lipid NOE observations. Furthermore, mutation of one of the key hydrophobic residues of KR-12 to Ala significantly reduced the antibacterial activity of the peptide mutants. These results illustrate that natural abundance heteronuclear-correlated NMR spectroscopy can be utilized to probe backbone structure and dynamics, and perhaps to map key membrane-binding residues of peptides in complex with micelles. (1)H-(13)Calpha HSQC wave, along with other NMR waves such as dipolar wave and chemical shift wave, offers novel insights into peptide-membrane interactions from different angles.

TALOS+: a hybrid method for predicting protein backbone torsion angles from NMR chemical shifts

NMR chemical shifts in proteins depend strongly on local structure. The program TALOS establishes an empirical relation between 13C, 15N and 1H chemical shifts and backbone torsion angles phi and psi (Cornilescu et al. J Biomol NMR 13 289-302, 1999). Extension of the original 20-protein database to 200 proteins increased the fraction of residues for which backbone angles could be predicted from 65 to 74%, while reducing the error rate from 3 to 2.5%. Addition of a two-layer neural network filter to the database fragment selection process forms the basis for a new program, TALOS+, which further enhances the prediction rate to 88.5%, without increasing the error rate. Excluding the 2.5% of residues for which TALOS+ makes predictions that strongly differ from those observed in the crystalline state, the accuracy of predicted phi and psi angles, equals +/-13 degrees . Large discrepancies between predictions and crystal structures are primarily limited to loop regions, and for the few cases where multiple X-ray structures are available such residues are often found in different states in the different structures. The TALOS+ output includes predictions for individual residues with missing chemical shifts, and the neural network component of the program also predicts secondary structure with good accuracy.

Relationship between chemical shift value and accessible surface area for all amino acid atoms

BACKGROUND

Chemical shifts obtained from NMR experiments are an important tool in determining secondary, even tertiary, protein structure. The main repository for chemical shift data is the BioMagResBank, which provides NMR-STAR files with this type of information. However, it is not trivial to link this information to available coordinate data from the PDB for non-backbone atoms due to atom and chain naming differences, as well as sequence numbering changes.

RESULTS

We here describe the analysis of a consistent set of chemical shift and coordinate data, in which we focus on the relationship between the per-atom solvent accessible surface area (ASA) in the reported coordinates and their reported chemical shift value. The data is available online on http://www.ebi.ac.uk/pdbe/docs/NMR/shiftAnalysis/index.html.

CONCLUSION

Atoms with zero per-atom ASA have a significantly larger chemical shift dispersion and often have a different chemical shift distribution compared to those that are solvent accessible. With higher per-atom ASA, the chemical shift values also tend towards random coil values. The per-atom ASA, although not the determinant of the chemical shift, thus provides a way to directly correlate chemical shift information to the atomic coordinates.