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PubMed2004

COMe: the ontology of bioinorganic proteins.

BACKGROUND: Many characterised proteins contain metal ions, small organic molecules or modified residues. In contrast, the huge amount of data generated by genome projects consists exclusively of sequences with almost no annotation. One of the goals of the structural genomics initiative is to provide representative three-dimensional (3-D) structures for as many protein/domain folds as possible to allow successful homology modelling. However, important functional features such as metal co-ordination or a type of prosthetic group are not always conserved in homologous proteins. So far, the problem of correct annotation of bioinorganic proteins has been largely ignored by the bioinformatics community and information on bioinorganic centres obtained by methods other than crystallography or NMR is only available in literature databases. RESULTS: COMe (Co-Ordination of Metals) represents the ontology for bioinorganic and other small molecule centres in complex proteins. COMe consists of three types of entities: 'bioinorganic motif' (BIM), 'molecule' (MOL), and 'complex proteins' (PRX), with each entity being assigned a unique identifier. A BIM consists of at least one centre (metal atom, inorganic cluster, organic molecule) and two or more endogenous and/or exogenous ligands. BIMs are represented as one-dimensional (1-D) strings and 2-D diagrams. A MOL entity represents a 'small molecule' which, when in complex with one or more polypeptides, forms a functional protein. The PRX entities refer to the functional proteins as well as to separate protein domains and subunits. The complex proteins in COMe are subdivided into three categories: (i) metalloproteins, (ii) organic prosthetic group proteins and (iii) modified amino acid proteins. The data are currently stored in both XML format and a relational database and are available at http://www.ebi.ac.uk/come/. CONCLUSION: COMe provides the classification of proteins according to their 'bioinorganic' features and thus is orthogonal to other classification schemes, such as those based on sequence similarity, 3-D fold, enzyme activity, or biological process. The hierarchical organisation of the controlled vocabulary allows both for annotation and querying at different levels of granularity.

Binding Sites↗
PubMed2002

Analysis of the proteome in the human pituitary.

The pituitary is the master endocrine gland responsible for the regulation of various physiologic and metabolic processes. Proteomics offers an efficient means for a comprehensive analysis of pituitary protein expression. This paper reports on the application of proteomics for the mapping of major proteins in a normal (control) pituitary. Pituitary proteins were separated by two-dimensional gel electrophoresis with immobilized pH 3-10 gradient strips. Major protein spots that were visualized in the two-dimensional gel by silver staining were excised, and the proteins in these spots were digested with trypsin. The tryptic digests were analyzed by mass spectrometry, and the mass spectrometric data were used to identify the proteins through searches of the SWISS-PROT or NCBInr protein sequence databases. The majority of the proteins were identified on the basis of peptide mass fingerprinting data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Several proteins were also characterized based on product-ion spectra measured by post-source decay analysis and/or liquid chromatography-electrospray-quadrupole ion trap mass spectrometry. To date, 62 prominent protein spots, corresponding to 38 different proteins, were identified. The identified proteins include important pituitary hormones, structural proteins, enzymes, and other proteins. The protein identification data were used to establish a two-dimensional reference database of the human pituitary, which can be accessed over the Internet (http://www.utmem.edu/proteomics). This database will serve as a tool for further proteomics studies of pituitary protein expression in health and disease.

Computational Biology↗
PubMed2007

Online workbenches for neural network connections.

The nervous system is the most complex object we know of. It is a spatially distributed, functionally differentiated network formed by axonal connections between defined neuron populations and effector cells. Computer science provides exciting new tools for archiving, analyzing, synthesizing, and modeling on the Web vast amounts of frequently conflicting and incomplete qualitative and quantitative data about the organization and molecular mechanisms of neural networks. To optimize conceptual advances in systems neuroscience, it is important for the research and publishing communities to embrace three exercises: using defined nomenclatures; populating databases; and providing feedback to developers about improved design, performance, and functionality of knowledge management systems and associated visualization tools.

Animals↗
PubMed2000

Virtual cloning and physical mapping of a human T-box gene, TBX4.

The Tbx2/3/4/5 subfamily is one of the largest subgroupings within the T-box gene family, the members of which encode developmentally critical transcription factors. TBX4, a human member of the Tbx2/3/4/5 subfamily, has been identified and characterized from a high-throughput genomic sequence. The genomic organization of TBX4 was elucidated by computational sequence analysis, and the putative cDNA sequence was assembled. The genomic organization of TBX4 is very similar to that of TBX5, as is the situation for TBX2 and TBX3. The physical configuration of the TBX4-TBX2 cluster on human chromosome 17q21-q22 is similar to that of the TBX5-TBX3 cluster on chromosome 12q23-q24. The assembled TBX4 cDNA sequence was searched against the EST databases, and a TBX4 EST was identified.

Base Sequence↗
PubMed2001

Experimental data of a single promoter can be used for in silico detection of genes with related regulation in the absence of sequence similarity.

Gene expression is presently a major focus in genome analysis, and the experimental data on regulatory mechanisms and functional transcription factor binding sites are steadily growing. However, the annotation of transcriptional regulation of sequences cannot keep pace with the exponential growth of sequence databases. Employing detailed experimental data of a single promoter or enhancer to predict genes with similar regulation would provide a powerful method to link the literature about transcriptional regulation and sequence databases. To this end, we used information on individual functional transcription factor binding sites to compose in silico promoter and enhancer models of muscle-specific genes and to analyze the rodents section of EMBL with these models. Exhaustive evaluation of all hits revealed every second to third match to be a muscle-associated gene. Moreover, functionally related regulatory regions were detected by our model-based approach even in the absence of sequence similarity. We believe that this new approach is a substanial extension to database analysis by BLAST or FASTA, which are restricted to sequence similarity.

Animals↗
PubMed1999

SECOST: sequence-conformation-structure database for amino acid residues in proteins.

The sequence-conformation-structure database for amino acid residues contains information on 114 828 individual residues derived from the spatial structures of 473 high-quality non-homologous proteins. The information in the database is obtained using a variety of different methods and can be used in various protein modeling applications.

Computational Biology↗
PubMed2004

APD: the Antimicrobial Peptide Database.

An antimicrobial peptide database (APD) has been established based on an extensive literature search. It contains detailed information for 525 peptides (498 antibacterial, 155 antifungal, 28 antiviral and 18 antitumor). APD provides interactive interfaces for peptide query, prediction and design. It also provides statistical data for a select group of or all the peptides in the database. Peptide information can be searched using keywords such as peptide name, ID, length, net charge, hydrophobic percentage, key residue, unique sequence motif, structure and activity. APD is a useful tool for studying the structure-function relationship of antimicrobial peptides. The database can be accessed via a web-based browser at the URL: http://aps.unmc.edu/AP/main.html.

Amino Acid Motifs↗
PubMed2004

TOPS: an enhanced database of protein structural topology.

The TOPS database holds topological descriptions of protein structures. These compact and highly abstract descriptions reduce the protein fold to a sequence of Secondary Structure Elements (SSEs) and three sets of pairwise relationships between them, hydrogen bonds relating parallel and anti- parallel beta strands, spatial adjacencies relating neighbouring SSEs, and the chiralities of selected supersecondary structures, including connections in betaalphabeta units and between parallel alpha helices. The database is used as a resource for visualizing folding topologies, fast topological pattern searching and structure comparison. Here, significant enhancements to the TOPS database are described. The topological description has been enhanced to include packing relationships between helices, which significantly improves the description of protein folds with little beta strand content. Further, the topological description has been annotated with sequence information. The query interfaces to the database have been improved and the new version can be found at http://www.tops.leeds.ac.uk/.

Animals↗
PubMed2006

FlyRNAi: the Drosophila RNAi screening center database.

RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21,000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database (http://flyRNAi.org/cgi-bin/RNAi_screens.pl) in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.

Animals↗
PubMed2006

AgdbNet - antigen sequence database software for bacterial typing.

BACKGROUND: Bacterial typing schemes based on the sequences of genes encoding surface antigens require databases that provide a uniform, curated, and widely accepted nomenclature of the variants identified. Due to the differences in typing schemes, imposed by the diversity of genes targeted, creating these databases has typically required the writing of one-off code to link the database to a web interface. Here we describe agdbNet, widely applicable web database software that facilitates simultaneous BLAST querying of multiple loci using either nucleotide or peptide sequences. RESULTS: Databases are described by XML files that are parsed by a Perl CGI script. Each database can have any number of loci, which may be defined by nucleotide and/or peptide sequences. The software is currently in use on at least five public databases for the typing of Neisseria meningitidis, Campylobacter jejuni and Streptococcus equi and can be set up to query internal isolate tables or suitably-configured external isolate databases, such as those used for multilocus sequence typing. The style of the resulting website can be fully configured by modifying stylesheets and through the use of customised header and footer files that surround the output of the script. CONCLUSION: The software provides a rapid means of setting up customised Internet antigen sequence databases. The flexible configuration options enable typing schemes with differing requirements to be accommodated.

Algorithms↗
PubMed1999

Organising multi-dimensional biological image information: the BioImage Database.

Nowadays it is possible to unravel complex information at all levels of cellular organization by obtaining multi-dimensional image information. At the macromolecular level, three-dimensional (3D) electron microscopy, together with other techniques, is able to reach resolutions at the nanometer or subnanometer level. The information is delivered in the form of 3D volumes containing samples of a given function, for example, the electron density distribution within a given macromolecule. The same situation happens at the cellular level with the new forms of light microscopy, particularly confocal microscopy, all of which produce biological 3D volume information. Furthermore, it is possible to record sequences of images over time (videos), as well as sequences of volumes, bringing key information on the dynamics of living biological systems. It is in this context that work on BioImage started two years ago, and that its first version is now presented here. In essence, BioImage is a database specifically designed to contain multi-dimensional images, perform queries and interactively work with the resulting multi-dimensional information on the World Wide Web, as well as accomplish the required cross-database links. Two sister home pages of BioImage can be accessed at http://www. bioimage.org and http://www-embl.bioimage.org

Bacterial Proteins↗
PubMed2001

The need for integrating neuronal morphology databases and computational environments in exploring neuronal structure and function.

Neurons connect to each other through a myriad of dendritic and axonal arborisations. Dendritic structures provide the substrate for integration of postsynaptic potentials and control of action potential generation. Axonal structures provide the substrate for action potential dissemination and signalling to target neurons. The morphological complexity of dendritic arborisations is assumed to play a critical role in the transformation of spatio-temporal patterns of postsynaptic potentials into time-structured series of action potentials. Although these transformations lie at the basis of information processing in the brain, it is still far from understood how their details are influenced by dendritic shape. To facilitate research in this area, it is necessary that data on both the morphology and electrical properties of neurons, as well as computational tools for analysis, become available in an integrated way. This requires a combined effort from the fields of informatics and neurosciences (together called neuroinformatics) in order to create data acquisition, databasing and computational tools. Focusing on neuronal morphology, this chapter will give a brief review of the current neuroinformatics developments in both reconstruction techniques, morphological quantification, modeling of morphological complexity, modeling of function and the need for databasing neuronal morphologies. Additionally, one of the dendritic modeling approaches is described in more detail in the Appendix.

Animals↗
PubMedDate not supplied

Developing an antituberculosis compounds database and data mining in the search of a motif responsible for the activity of a diverse class of antituberculosis agents.

A novel data mining procedure to look for new antitubercular agents and targets as well as to find a minimum common bioactive substructure (MCBS), has been reported here. The methodology extracts MCBS, both across the diverse chemical classes and within the particular chemical class, known to be present in the various marketed drugs alongside antimycobacterial compounds with known MICs. For this purpose a small in-house database of compounds has been created, for which MICs against Mycobacterium are known. The compounds have been collected from literature available on the synthetic compounds, having known MICs against Mycobacterium tuberculosis. An elaborate HQSAR (Hologram QSAR) study has been attempted to extract active fragment from a diverse class of compounds, in combination with the clustering technique to select a homogeneous group of compounds having good a profile toward the activity. The 2D pharmacophore (the 2D fragments extracted from HQSAR) has been validated searching the database. It has been found further that this validated 2D pharmacophore could be used for searching the orphan target in Mycobacterium effectively.

Antitubercular Agents↗
PubMed2002

Interactive InterPro-based comparisons of proteins in whole genomes.

MOTIVATION: The SWISS-PROT group at the EBI has developed the Proteome Analysis Database utilizing existing resources and providing comprehensive and integrated comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes. The Proteome Analysis Database is accompanied by a program that has been designed to carry out interactive InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Computational Biology↗
PubMed2004

topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association.

The database of topographic mapping of Single Nucleotide Polymorphism (topoSNP) provides an online resource for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. The current release also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data. The database will be updated at regular intervals and can be accessed at: http://gila.bioengr.uic.edu/snp/toposnp.

Computational Biology↗
PubMed2006

BBP: Brucella genome annotation with literature mining and curation.

BACKGROUND: Brucella species are Gram-negative, facultative intracellular bacteria that cause brucellosis in humans and animals. Sequences of four Brucella genomes have been published, and various Brucella gene and genome data and analysis resources exist. A web gateway to integrate these resources will greatly facilitate Brucella research. Brucella genome data in current databases is largely derived from computational analysis without experimental validation typically found in peer-reviewed publications. It is partially due to the lack of a literature mining and curation system able to efficiently incorporate the large amount of literature data into genome annotation. It is further hypothesized that literature-based Brucella gene annotation would increase understanding of complicated Brucella pathogenesis mechanisms. RESULTS: The Brucella Bioinformatics Portal (BBP) is developed to integrate existing Brucella genome data and analysis tools with literature mining and curation. The BBP InterBru database and Brucella Genome Browser allow users to search and analyze genes of 4 currently available Brucella genomes and link to more than 20 existing databases and analysis programs. Brucella literature publications in PubMed are extracted and can be searched by a TextPresso-powered natural language processing method, a MeSH browser, a keywords search, and an automatic literature update service. To efficiently annotate Brucella genes using the large amount of literature publications, a literature mining and curation system coined Limix is developed to integrate computational literature mining methods with a PubSearch-powered manual curation and management system. The Limix system is used to quickly find and confirm 107 Brucella gene mutations including 75 genes shown to be essential for Brucella virulence. The 75 genes are further clustered using COG. In addition, 62 Brucella genetic interactions are extracted from literature publications. These results make possible more comprehensive investigation of Brucella pathogenesis. Other BBP features include publication email alert service, Brucella researchers' contact database, and discussion forum. CONCLUSION: BBP is a gateway for Brucella researchers to search, analyze, and curate Brucella genome data originated from public databases and literature. Brucella gene mutations and genetic interactions are annotated using Limix leading to better understanding of Brucella pathogenesis.

Algorithms↗
PubMed2003

Databases and data mining for computational vaccinology.

Drugs and vaccines are keys to the effective fight against disease. While the pharmaceutical industry has developed an awesome array of real and virtual approaches to rational drug discovery, the complexity of the immune system hampers attempts to design and develop vaccines in a rational manner. The goal of immunoinformatics (the application of informatics techniques to immunological macromolecules), an emergent sub-discipline of bioinformatics, is to develop computational vaccinology as a potent tool in the quest for new vaccines. Databases and data mining, the two principal weapons at the disposal of the in silico vaccinologist, will be presented in the light of current developments.

Computational Biology↗