Motivation: Residue-residue contact prediction through direct coupling analysis has reached impressive accuracy, but yet higher accuracy will be needed to allow for routine modelling of protein structures. One way to improve the prediction accuracy is to filter predicted contacts using knowledge about the particular protein of interest or knowledge about protein structures in general. Results: We focus on the latter and discuss a set of filters that can be used to remove false positive contact predictions. Each filter depends on one or a few cut-off parameters for which the filter performance was investigated. Combining all filters while using default parameters resulted for a test set of 851 protein domains in the removal of 29% of the predictions of which 92% were indeed false positives. Availability and implementation: All data and scripts are available at http://comprec-lin.iiar.pwr.edu.pl/FPfilter/. Supplementary information: Supplementary data are available at Bioinformatics online.

MOTIVATION: Apart from meta-predictors, most of today's methods for residue-residue contact prediction are based entirely on Direct Coupling Analysis (DCA) of correlated mutations in multiple sequence alignments (MSAs). These methods are on average ∼40% correct for the 100 strongest predicted contacts in each protein. The end-user who works on a single protein of interest will not know if predictions are either much more or much less correct than 40%, which is especially a problem if contacts are predicted to steer experimental research on that protein. RESULTS: We designed a regression model that forecasts the accuracy of residue-residue contact prediction for individual proteins with an average error of 7 percentage points. Contacts were predicted with two DCA methods (gplmDCA and PSICOV). The models were built on parameters that describe the MSA, the predicted secondary structure, the predicted solvent accessibility and the contact prediction scores for the target protein. Results show that our models can be also applied to the meta-methods, which was tested on RaptorX. AVAILABILITY AND IMPLEMENTATION: All data and scripts are available from http://comprec-lin.iiar.pwr.edu.pl/dcaQ/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The recently developed direct coupling analysis (DCA) method has greatly improved the accuracy with which residue-residue contacts can be predicted from multiple sequence alignments. Contact prediction accuracy, though, is still often not sufficient for complete ab initio protein structure prediction. DCA can, however, support protein structure studies in several ways. RESULTS: We show that DCA can select the better structure from among properly folded and misfolded variants. This idea was tested by comparing obsolete PDB files with their more correctly folded successors and by the comparison of structures with deliberately misfolded decoy models from the Decoys 'R' Us database. The DCA method systematically predicts more contacts for properly folded structures than for misfolded ones. The method works much better for X-ray structures than for NMR structures. AVAILABILITY AND IMPLEMENTATION: All data are available from http://comprec-lin.iiar.pwr.edu.pl/dcaVSmisfolds/ and http://swift.cmbi.ru.nl/dcaVSmisfolds/ . CONTACT: [email protected] . SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Intrinsically disordered proteins (IDPs) lack tertiary structure and thus differ from globular proteins in terms of their sequence-structure-function relations. IDPs have lower sequence conservation, different types of active sites and a different distribution of functionally important regions, which altogether make their multiple sequence alignment (MSA) difficult. The KMAD MSA software has been written specifically for the alignment and annotation of IDPs. It augments the substitution matrix with knowledge about post-translational modifications, functional domains and short linear motifs. RESULTS: MSAs produced with KMAD describe well-conserved features among IDPs, tend to agree well with biological intuition, and are a good basis for designing new experiments to shed light on this large, understudied class of proteins. AVAILABILITY AND IMPLEMENTATION: KMAD web server is accessible at http://www.cmbi.ru.nl/kmad/ A standalone version is freely available. CONTACT: [email protected].

SUMMARY: Today's graphics processing units (GPUs) compose the scene from individual triangles. As about 320 triangles are needed to approximate a single sphere-an atom-in a convincing way, visualizing larger proteins with atomic details requires tens of millions of triangles, far too many for smooth interactive frame rates. We describe a new approach to solve this 'molecular graphics problem', which shares the work between GPU and multiple CPU cores, generates high-quality results with perfectly round spheres, shadows and ambient lighting and requires only OpenGL 1.0 functionality, without any pixel shader Z-buffer access (a feature which is missing in most mobile devices). AVAILABILITY AND IMPLEMENTATION: YASARA View, a molecular modeling program built around the visualization algorithm described here, is freely available (including commercial use) for Linux, MacOS, Windows and Android (Intel) from www.YASARA.org. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: The ever on-going technical developments in Next Generation Sequencing have led to an increase in detected disease related mutations. Many bioinformatics approaches exist to analyse these variants, and of those the methods that use 3D structure information generally outperform those that do not use this information. 3D structure information today is available for about twenty percent of the human exome, and homology modelling can double that fraction. This percentage is rapidly increasing so that we can expect to analyse the majority of all human exome variants in the near future using protein structure information. RESULTS: We collected a test dataset of well-described mutations in proteins for which 3D-structure information is available. This test dataset was used to analyse the possibilities and the limitations of methods based on sequence information alone, hybrid methods, machine learning based methods, and structure based methods. CONCLUSIONS: Our analysis shows that the use of structural features improves the classification of mutations. This study suggests strategies for future analyses of disease causing mutations, and it suggests which bioinformatics approaches should be developed to make progress in this field.

The WeNMR ( http://www.wenmr.eu ) project is a European Union funded international effort to streamline and automate analysis of Nuclear Magnetic Resonance (NMR) and Small Angle X-Ray scattering (SAXS) imaging data for atomic and near-atomic resolution molecular structures. Conventional calculation of structure requires the use of various software packages, considerable user expertise and ample computational resources. To facilitate the use of NMR spectroscopy and SAXS in life sciences the WeNMR consortium has established standard computational workflows and services through easy-to-use web interfaces, while still retaining sufficient flexibility to handle more specific requests. Thus far, a number of programs often used in structural biology have been made available through application portals. The implementation of these services, in particular the distribution of calculations to a Grid computing infrastructure, involves a novel mechanism for submission and handling of jobs that is independent of the type of job being run. With over 450 registered users (September 2012), WeNMR is currently the largest Virtual Organization (VO) in life sciences. With its large and worldwide user community, WeNMR has become the first Virtual Research Community officially recognized by the European Grid Infrastructure (EGI).

MOTIVATION: Macromolecular crystal structures in the Protein Data Bank (PDB) are a key source of structural insight into biological processes. These structures, some >30 years old, were constructed with methods of their era. With PDB_REDO, we aim to automatically optimize these structures to better fit their corresponding experimental data, passing the benefits of new methods in crystallography on to a wide base of non-crystallographer structure users. RESULTS: We developed new algorithms to allow automatic rebuilding and remodeling of main chain peptide bonds and side chains in crystallographic electron density maps, and incorporated these and further enhancements in the PDB_REDO procedure. Applying the updated PDB_REDO to the oldest, but also to some of the newest models in the PDB, corrects existing modeling errors and brings these models to a higher quality, as judged by standard validation methods. AVAILABILITY AND IMPLEMENTATION: The PDB_REDO database and links to all software are available at http://www.cmbi.ru.nl/pdb_redo. CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed. RESULTS: We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article. CONCLUSIONS: This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources.

SUMMARY: Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers. AVAILABILITY AND IMPLEMENTATION: The GPCR-OKB web application is freely available at http://www.gpcr-okb.org

BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. RESULTS: In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. CONCLUSIONS: We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background.

SUMMARY: The EMBRACE Registry is a web portal that collects and monitors web services according to test scripts provided by the their administrators. Users are able to search for, rank and annotate services, enabling them to select the most appropriate working service for inclusion in their bioinformatics analysis tasks. AVAILABILITY AND IMPLEMENTATION: Web site implemented with PHP, Python, MySQL and Apache, with all major browsers supported. (www.embraceregistry.net).

MOTIVATION: Recent advances in sequencing techniques have yielded enormous amounts of protein sequence data from various species. This large dataset allows sequence comparison between paralogous and orthologous proteins to identify motifs or functional positions that account for the differences of functional subgroups ('specificity' positions). Algorithms such as SDPpred and the two-entropies analysis (TEA) have been developed to detect such specificity positions from a multiple sequence alignment (MSA) grouped into classes according to certain biological functions. Other algorithms such as TreeDet compute a classification and then predict specificity positions associated with it. However, there are still many unresolved questions: Was the optimal subdivision of a protein family achieved? Do the definitions at different levels of the phylogenetic tree affect the prediction of specificity positions? Can the whole phylogenetic tree be used instead of only one level in it to predict specificity positions? RESULTS: Here we present a novel method, TEA-O (Two-entropies analysis-Objective), to trace the evolutionary pressure from the root to the branches of the phylogenetic tree. At each level of the tree, a TEA plot is produced to capture the signal of the evolutionary pressure. A consensus TEA-O plot is composed from the whole series of plots to provide a condensed representation. Positions related to functions that evolved early (conserved) or later (specificity) are close to the lower-left or upper-left corner of the TEA-O plot, respectively. This novel approach allows an unbiased, user-independent, analysis of residue relevance in a protein family. We compared our TEA-O method with various algorithms using both synthetic and real protein sequences. The results show that our method is robust, sensitive to subtle differences in evolutionary pressure during evolution and comprehensive because all positions in the MSA are presented in the consensus plot. AVAILABILITY: All computer programs and datasets used in this work are available at http://nava.liacs.nl/kye/TEA-O/ for academic use.

BACKGROUND: G Protein-Coupled Receptors (GPCRs) are a large and diverse family of membrane proteins whose members participate in the regulation of most cellular and physiological processes and therefore represent key pharmacological targets. Although several bioinformatics resources support research on GPCRs, most of these have been designed based on the traditional assumption that monomeric GPCRs constitute the functional receptor unit. The increase in the frequency and number of reports about GPCR dimerization/oligomerization and the implication of oligomerization in receptor function makes necessary the ability to store and access information about GPCR dimers/oligomers electronically. RESULTS: We present here the requirements and ontology (the information scheme to describe oligomers and associated concepts and their relationships) for an information system that can manage the elements of information needed to describe comprehensively the phenomena of both homo- and hetero-oligomerization of GPCRs. The comprehensive information management scheme that we plan to use for the development of an intuitive and user-friendly GPCR-Oligomerization Knowledge Base (GPCR-OKB) is the result of a community dialog involving experimental and computational colleagues working on GPCRs. CONCLUSION: Our long term goal is to disseminate to the scientific community organized, curated, and detailed information about GPCR dimerization/oligomerization and its related structural context. This information will be reported as close to the data as possible so the user can make his own judgment on the conclusions drawn for a particular study. The requirements and ontology described here will facilitate the development of future information systems for GPCR oligomers that contain both computational and experimental information about GPCR oligomerization. This information is freely accessible at http://www.gpcr-okb.org.

BACKGROUND: A wide range of research areas in bioinformatics, molecular biology and medicinal chemistry require precise chemical structure information about molecules and reactions, e.g. drug design, ligand docking, metabolic network reconstruction, and systems biology. Most available databases, however, treat chemical structures more as illustrations than as a datafield in its own right. Lack of chemical accuracy impedes progress in the areas mentioned above. We present a database of metabolites called BioMeta that augments the existing pathway databases by explicitly assessing the validity, correctness, and completeness of chemical structure and reaction information. DESCRIPTION: The main bulk of the data in BioMeta were obtained from the KEGG Ligand database. We developed a tool for chemical structure validation which assesses the chemical validity and stereochemical completeness of a molecule description. The validation tool was used to examine the compounds in BioMeta, showing that a relatively small number of compounds had an incorrect constitution (connectivity only, not considering stereochemistry) and that a considerable number (about one third) had incomplete or even incorrect stereochemistry. We made a large effort to correct the errors and to complete the structural descriptions. A total of 1468 structures were corrected and/or completed. We also established the reaction balance of the reactions in BioMeta and corrected 55% of the unbalanced (stoichiometrically incorrect) reactions in an automatic procedure. The BioMeta database was implemented in PostgreSQL and provided with a web-based interface. CONCLUSION: We demonstrate that the validation of metabolite structures and reactions is a feasible and worthwhile undertaking, and that the validation results can be used to trigger corrections and improvements to BioMeta, our metabolite database. BioMeta provides some tools for rational drug design, reaction searches, and visualization. It is freely available at http://www.cmbi.ru.nl/biometa/ provided that the copyright notice of all original data is cited. The database will be useful for querying and browsing biochemical pathways, and to obtain reference information for identifying compounds. However, these applications require that the underlying data be correct, and that is the focus of BioMeta.

One of the major goals of structural genomics projects is to determine the three-dimensional structure of representative members of as many different fold families as possible. Comparative modeling is expected to fill the remaining gaps by providing structural models of homologs of the experimentally determined proteins. However, for such an approach to be successful it is essential that the quality of the experimentally determined structures is adequate. In an attempt to build a homology model for the protein dynein light chain 2A (DLC2A) we found two potential templates, both experimentally determined nuclear magnetic resonance (NMR) structures originating from structural genomics efforts. Despite their high sequence identity (96%), the folds of the two structures are markedly different. This urged us to perform in-depth analyses of both structure ensembles and the deposited experimental data, the results of which clearly identify one of the two models as largely incorrect. Next, we analyzed the quality of a large set of recent NMR-derived structure ensembles originating from both structural genomics projects and individual structure determination groups. Unfortunately, a visual inspection of structures exhibiting lower quality scores than DLC2A reveals that the seriously flawed DLC2A structure is not an isolated incident. Overall, our results illustrate that the quality of NMR structures cannot be reliably evaluated using only traditional experimental input data and overall quality indicators as a reference and clearly demonstrate the urgent need for a tight integration of more sophisticated structure validation tools in NMR structure determination projects. In contrast to common methodologies where structures are typically evaluated as a whole, such tools should preferentially operate on a per-residue basis.

SUMMARY: Residue-based diagrams of proteins are graphical representations that can be used in protein information systems. These diagrams make it possible to visually integrate different types of biological information. The approach has been used successfully for membrane proteins. We developed the Residue-based diagram generator to (i) make it possible to generate residue-based diagrams of proteins in a batch mode that is compatible with the needs of information system curators, (ii) allow the generation of residue-based diagrams for families of soluble proteins or domains. AVAILABILITY: Licensed. Royalty free licenses are granted to non-profit institutions for educational and research purposes. http://icb.mssm.edu/crt/RbDg/index.xml

MOTIVATION: Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. RESULTS: We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.

MOTIVATION: Homology modeling is rapidly becoming the method of choice for obtaining three-dimensional coordinates for proteins because genome projects produce sequences at a much higher rate than NMR and X-ray laboratories can solve the three-dimensional structures. The quality of protein models will not be immediately clear to novices and support with the evaluation seems to be needed. Expert users are sometimes interested in evaluating the quality of modeling programs rather than the quality of the models themselves. RESULTS: Three servers have been made available to the scientific community: a homology modeling server, a model quality evaluation server and a server that evaluates models built of proteins for which the structure is already known, thereby implicitly evaluating the quality of the modeling program. AVAILABILITY: The modeling-related servers and several structure analysis servers are freely available at http://swift.embl-heidelberg.de/servers/ CONTACT: [email protected]

Statistical methods that compare observed and expected distributions of experimental observables provide powerful tools for the quality control of protein structures. The distribution of backbone dihedral angles (‘Ramachandran plot’) has often been used for such quality control, but without a firm statistical foundation. A new and simple method is presented for judging the quality of a protein structure based on the distribution of backbone dihedral angles. Inputs to the method are 60 torsion angle distributions extracted from protein structures solved at high resolution; one for each combination of residue type and tri-state secondary structure. Output for a protein is a Ramachandran Z-score, expressing the quality of the Ramachandran plot relative to current state-of-the-art structures. The Ramachandran test is available as part of the free WHAT_CHECK program. Information about this program can be obtained on the WWW from http://swift.embl-heidelberg.de/whatcheck/ E-mail: [email protected]

MOTIVATION: The Protein Data Bank currently contains more than 4700 protein coordinate sets. It is often desirable to make a selection from these files based on a criterion like R-factor, experimental method, length of the amino acid sequence, or the number of homologous sequences in SWISSPROT. Doing this using the distributed form of the Protein Data Bank can be a tedious task, because (1) this requires reading one file for every single entry, and (2) not all of the information is present in a consistent computer readable way in all of the entries. RESULTS: The PDBFINDER database provides an easy to interpret file containing summary information about all Protein Data Bank files. Summary information from the DSSP (Definition of Secondary Structure of Proteins) and HSSP (Homology derived Secondary Structure of Proteins) databases is also included. Furthermore, where essential data were missing from the Protein Data Bank file, this information has been retrieved from the original literature. AVAILABILITY: The latest version of the PDBFINDER database can be downloaded by anonymous ftp from swift.embl-heidelberg.de, directory:/pdbfinder. CONTACT: E-mail address [email protected].