TRIAL: a tool for finding distant structural similarities

Finding structural similarities in distantly related proteins can reveal functional relationships that can not be identified using sequence comparison. Given two proteins A and B and threshold ε ?, we develop an algorithm, TRiplet-based Iterative ALignment (TRIAL) for computing the transformation of B that maximizes the number of aligned residues such that the root mean square deviation (RMSD) of the alignment is at most ε ?. Our algorithm is designed with the specific goal of effectively handling proteins with low similarity in primary structure, where existing algorithms perform particularly poorly. Experiments show that our method outperforms existing methods. TRIAL alignment brings the secondary structures of distantly related proteins to similar orientations. It also finds larger number of secondary structure matches at lower RMSD values and increased overall alignment lengths. Its classification accuracy is up to 63 percent better than other methods, including CE and DALI. TRIAL successfully aligns 83 percent of the residues from the smaller protein in reasonable time while other methods align only 29 to 65 percent of the residues for the same set of proteins.     

Metalloproteomics: high-throughput structural and functional annotation of proteins in structural genomics

A high-throughput method for measuring transition metal content based on quantitation of X-ray fluorescence signals was used to analyze 654 proteins selected as targets by the New York Structural GenomiX Research Consortium. Over 10% showed the presence of transition metal atoms in stoichiometric amounts; these totals as well as the abundance distribution are similar to those of the Protein Data Bank. Bioinformatics analysis of the identified metalloproteins in most cases supported the metalloprotein annotation; identification of the conserved metal binding motif was also shown to be useful in verifying structural models of the proteins. Metalloproteomics provides a rapid structural and functional annotation for these sequences and is shown to be approximately 95% accurate in predicting the presence or absence of stoichiometric metal content. The project's goal is to assay at least 1 member from each Pfam family; approximately 500 Pfam families have been characterized with respect to transition metal content so far.     

myMIR: a genome-wide microRNA targets identification and annotation tool

miRNA target genes prediction represents a crucial step in miRNAs functional characterization. In this context, the challenging issue remains predictions accuracy and recognition of false positive results. In this article myMIR, a web based system for increasing reliability of miRNAs predicted targets lists, is presented. myMIR implements an integrated pipeline for computing ranked miRNA::target lists and provides annotations for narrowing them down. The system relies on knowledge base data, suitably integrated in order to extend the functional characterization of targeted genes to miRNAs, by highlighting the search on over-represented annotation terms. Validation results show a dramatic reduction in the quantity of predictions and an increase in the sensitivity, when compared to other methods. This improves the predictions accuracy and allows the formulation of novel hypotheses on miRNAs functional involvement.     

Functional differentiation of proteins: implications for structural genomics

Structural genomics is a broad initiative of various centers aiming to provide complete coverage of protein structure space. Because it is not feasible to experimentally determine the structures of all proteins, it is generally agreed that the only viable strategy to achieve such coverage is to carefully select specific proteins (targets), determine their structure experimentally, and then use comparative modeling techniques to model the rest. Here we suggest that structural genomics centers refine the structure-driven approach in target selection by adopting function-based criteria. We suggest targeting functionally divergent superfamilies within a given structural fold so that each function receives a structural characterization. We have developed a method to do so, and an itemized survey of several functionally rich folds shows that they are only partially functionally characterized. We call upon structural genomics centers to consider this approach and upon computational biologists to further develop function-based targeting methods.     

Functional genomics as a tool in virus research

Genomics is the study of an organism’s entire genome. It started out as a great scientific endeavor in the 1990s which aimed to sequence the complete genomes of certain biological species. However viruses are not new to this field as complete viral genomes have routinely been sequenced since the past thirty years. The ‘genomic era’ has been said to have revolutionized biology. This knowledge of full genomes has created the field of functional genomics in today’s post-genomic era, which, is in most part concerned with the studies on the expression of the organism’s genome under different conditions. This article is an attempt to introduce its readers to the application of functional genomics to address and answer several complex biological issues in virus research.     

SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap

SUMMARY: The interpretation of genome-wide association results is confounded by linkage disequilibrium between nearby alleles. We have developed a flexible bioinformatics query tool for single-nucleotide polymorphisms (SNPs) to identify and to annotate nearby SNPs in linkage disequilibrium (proxies) based on HapMap. By offering functionality to generate graphical plots for these data, the SNAP server will facilitate interpretation and comparison of genome-wide association study results, and the design of fine-mapping experiments (by delineating genomic regions harboring associated variants and their proxies). AVAILABILITY: SNAP server is available at http://www.broad.mit.edu/mpg/snap/.     

Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research

SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. AVAILABILITY: Blast2GO is freely available via Java Web Start at http://www.blast2go.de. SUPPLEMENTARY MATERIAL: http://www.blast2go.de -> Evaluation.     

yrGATE: a web-based gene-structure annotation tool for the identification and dissemination of eukaryotic genes

Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at .     

Structural proteomics: a tool for genome annotation

In any newly sequenced genome, 30% to 50% of genes encode proteins with unknown molecular or cellular function. Fortunately, structural genomics is emerging as a powerful approach of functional annotation. Because of recent developments in high-throughput technologies, ongoing structural genomics projects are generating new structures at an unprecedented rate. In the past year, structural studies have identified many new structural motifs involved in enzymatic catalysis or in binding ligands or other macromolecules (DNA, RNA, protein). The efficiency by which function is deduced from structure can be further improved by the integration of structure with bioinformatics and other experimental approaches, such as screening for enzymatic activity or ligand binding.     

The SOFG Anatomy Entry List (SAEL): an annotation tool for functional genomics data

A great deal of data in functional genomics studies needs to be annotated with low-resolution anatomical terms. For example, gene expression assays based on manually dissected samples (microarray, SAGE, etc.) need high-level anatomical terms to describe sample origin. First-pass annotation in high-throughput assays (e.g. large-scale in situ gene expression screens or phenotype screens) and bibliographic applications, such as selection of keywords, would also benefit from a minimum set of standard anatomical terms. Although only simple terms are required, the researcher faces serious practical problems of inconsistency and confusion, given the different aims and the range of complexity of existing anatomy ontologies. A Standards and Ontologies for Functional Genomics (SOFG) group therefore initiated discussions between several of the major anatomical ontologies for higher vertebrates. As we report here, one result of these discussions is a simple, accessible, controlled vocabulary of gross anatomical terms, the SOFG Anatomy Entry List (SAEL). The SAEL is available from http://www.sofg.org and is intended as a resource for biologists, curators, bioinformaticians and developers of software supporting functional genomics. It can be used directly for annotation in the contexts described above. Importantly, each term is linked to the corresponding term in each of the major anatomy ontologies. Where the simple list does not provide enough detail or sophistication, therefore, the researcher can use the SAEL to choose the appropriate ontology and move directly to the relevant term as an entry point. The SAEL links will also be used to support computational access to the respective ontologies.     

LFM-Pro: a tool for detecting significant local structural sites in proteins

MOTIVATION: The rapidly growing protein structure repositories have opened up new opportunities for discovery and analysis of functional and evolutionary relationships among proteins. Detecting conserved structural sites that are unique to a protein family is of great value in identification of functionally important atoms and residues. Currently available methods are computationally expensive and fail to detect biologically significant local features. RESULTS: We propose Local Feature Mining in Proteins (LFM-Pro) as a framework for automatically discovering family-specific local sites and the features associated with these sites. Our method uses the distance field to backbone atoms to detect geometrically significant structural centers of the protein. A feature vector is generated from the geometrical and biochemical environment around these centers. These features are then scored using a statistical measure, for their ability to distinguish a family of proteins from a background set of unrelated proteins, and successful features are combined into a representative set for the protein family. The utility and success of LFM-Pro are demonstrated on trypsin-like serine proteases family of proteins and on a challenging classification dataset via comparison with DALI. The results verify that our method is successful both in identifying the distinctive sites of a given family of proteins, and in classifying proteins using the extracted features. AVAILABILITY: The software and the datasets are freely available for academic research use at http://bioinfo.ceng.metu.edu.tr/Pub/LFMPro.     

Iterative ACORN as a high throughput tool in structural genomics

High throughput macromolecular structure determination is very essential in structural genomics as the available number of sequence information far exceeds the number of available 3D structures. ACORN, a freely available resource in the CCP4 suite of programs is a comprehensive and efficient program for phasing in the determination of protein structures, when atomic resolution data are available. ACORN with the automatic model-building program ARP/wARP and refinement program REFMAC is a suitable combination for the high throughput structural genomics. ACORN can also be run with secondary structural elements like helices and sheets as inputs with high resolution data. In situations, where ACORN phasing is not sufficient for building the protein model, the fragments (incomplete model/dummy atoms) can again be used as a starting input. Iterative ACORN is proved to work efficiently in the subsequent model building stages in congerin (PDB-ID: lis3) and catalase (PDB-ID: 1gwe) for which models are available.     

Target selection and annotation for the structural genomics of the amidohydrolase and enolase superfamilies

To study the substrate specificity of enzymes, we use the amidohydrolase and enolase superfamilies as model systems; members of these superfamilies share a common TIM barrel fold and catalyze a wide range of chemical reactions. Here, we describe a collaboration between the Enzyme Specificity Consortium (ENSPEC) and the New York SGX Research Center for Structural Genomics (NYSGXRC) that aims to maximize the structural coverage of the amidohydrolase and enolase superfamilies. Using sequence- and structure-based protein comparisons, we first selected 535 target proteins from a variety of genomes for high-throughput structure determination by X-ray crystallography; 63 of these targets were not previously annotated as superfamily members. To date, 20 unique amidohydrolase and 41 unique enolase structures have been determined, increasing the fraction of sequences in the two superfamilies that can be modeled based on at least 30% sequence identity from 45% to 73%. We present case studies of proteins related to uronate isomerase (an amidohydrolase superfamily member) and mandelate racemase (an enolase superfamily member), to illustrate how this structure-focused approach can be used to generate hypotheses about sequence–structure–function relationships. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

antibacTR: dynamic antibacterial-drug-target ranking integrating comparative genomics,structural analysis and experimental annotation

Background

Development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field. The last decades have seen a substantial decrease in the discovery of novel antibiotics, which combined with the recent thrive of multi-drug-resistant pathogens have generated a scenario of general concern. The procedures involved in the discovery and development of novel antibiotics are economically challenging, time consuming and lack any warranty of success. Furthermore, the return-on-investment for an antibacterial drug is usually marginal when compared to other therapeutics, which in part explains the decrease of private investment.

Results

In this work we present antibacTR, a computational pipeline designed to aid researchers in the selection of potential drug targets, one of the initial steps in antibacterial-drug discovery. The approach was designed and implemented as part of two publicly funded initiatives aimed at discovering novel antibacterial targets, mechanisms and drugs for a priority list of Gram-negative pathogens: Acinetobacter baumannii, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. However, at present this list has been extended to cover a total of 74 fully sequenced Gram-negative pathogens. antibacTR is based on sequence comparisons and queries to multiple databases (e.g. gene essentiality, virulence factors) to rank proteins according to their potential as antibacterial targets. The dynamic ranking of potential drug targets can easily be executed, customized and accessed by the user through a web interface which also integrates computational analyses performed in-house and visualizable on-site. These include three-dimensional modeling of protein structures and prediction of active sites among other functionally relevant ligand-binding sites.

Conclusions

Given its versatility and ease-of-use at integrating both experimental annotation and computational analyses, antibacTR may effectively assist microbiologists, medicinal-chemists and other researchers working in the field of antibacterial drug-discovery. The public web-interface for antibacTR is available at ‘http://bioinf.uab.cat/antibactr’.     

Bioverse: Functional,structural and contextual annotation of proteins and proteomes

Functional annotation is routinely performed for large-scale genomics projects and databases. Researchers working on more specific problems, for instance on an individual pathway or complex, also need to be able to quickly, completely and accurately annotate sequences. The Bioverse sequence annotation server (http://bioverse.compbio.washington.edu) provides a web-based interface to allow users to submit protein sequences to the Bioverse framework. Sequences are functionally and structurally annotated and potential contextual annotations are provided. Researchers can also submit candidate genomes for annotation of all proteins encoded by the genome (proteome).