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PubMed2006

DrugBank: a comprehensive resource for in silico drug discovery and exploration.

DrugBank is a unique bioinformatics/cheminformatics resource that combines detailed drug (i.e. chemical) data with comprehensive drug target (i.e. protein) information. The database contains >4100 drug entries including >800 FDA approved small molecule and biotech drugs as well as >3200 experimental drugs. Additionally, >14,000 protein or drug target sequences are linked to these drug entries. Each DrugCard entry contains >80 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data. Many data fields are hyperlinked to other databases (KEGG, PubChem, ChEBI, PDB, Swiss-Prot and GenBank) and a variety of structure viewing applets. The database is fully searchable supporting extensive text, sequence, chemical structure and relational query searches. Potential applications of DrugBank include in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. DrugBank is available at http://redpoll.pharmacy.ualberta.ca/drugbank/.

Computational Biology↗

PubMed2005

The value of short amino acid sequence matches for prediction of protein allergenicity.

Typically, genetically engineered crops contain traits encoded by one or a few newly expressed proteins. The allergenicity assessment of newly expressed proteins is an important component in the safety evaluation of genetically engineered plants. One aspect of this assessment involves sequence searches that compare the amino acid sequence of the protein to all known allergens. Analyses are performed to determine the potential for immunologically based cross-reactivity where IgE directed against a known allergen could bind to the protein and elicit a clinical reaction in sensitized individuals. Bioinformatic searches are designed to detect global sequence similarity and short contiguous amino acid sequence identity. It has been suggested that potential allergen cross-reactivity may be predicted by identifying matches as short as six to eight contiguous amino acids between the protein of interest and a known allergen. A series of analyses were performed, and match probabilities were calculated for different size peptides to determine if there was a scientifically justified search window size that identified allergen sequence characteristics. Four probability modeling methods were tested: (1) a mock protein and a mock allergen database, (2) a mock protein and genuine allergen database, (3) a genuine allergen and genuine protein database, and (4) a genuine allergen and genuine protein database combined with a correction for repeating peptides. These analyses indicated that searches for short amino acid sequence matches of eight amino acids or fewer to identify proteins as potential cross-reactive allergens is a product of chance and adds little value to allergy assessments for newly expressed proteins.

Allergens↗

PubMed2006

AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies.

BACKGROUND: Monoclonal antibodies are used extensively throughout the biomedical sciences for detection of antigens, either in vitro or in vivo. We, for example, have used them for quantitation of proteins on "reverse-phase" protein lysate arrays. For those studies, we quality-controlled > 600 available monoclonal antibodies and also needed to develop precise information on the genes that encode their antigens. Translation among the various protein and gene identifier types proved non-trivial because of one-to-many and many-to-one relationships. To organize the antibody, protein, and gene information, we initially developed a relational database in Filemaker for our own use. When it became apparent that the information would be useful to many other researchers faced with the need to choose or characterize antibodies, we developed it further as AbMiner, a fully relational web-based database under MySQL, programmed in Java. DESCRIPTION: AbMiner is a user-friendly, web-based relational database of information on > 600 commercially available antibodies that we validated by Western blot for protein microarray studies. It includes many types of information on the antibody, the immunogen, the vendor, the antigen, and the antigen's gene. Multiple gene and protein identifier types provide links to corresponding entries in a variety of other public databases, including resources for phosphorylation-specific antibodies. AbMiner also includes our quality-control data against a pool of 60 diverse cancer cell types (the NCI-60) and also protein expression levels for the NCI-60 cells measured using our high-density "reverse-phase" protein lysate microarrays for a selection of the listed antibodies. Some other available database resources give information on antibody specificity for one or a couple of cell types. In contrast, the data in AbMiner indicate specificity with respect to the antigens in a pool of 60 diverse cell types from nine different tissues of origin. CONCLUSION: AbMiner is a relational database that provides extensive information from our own laboratory and other sources on more than 600 available antibodies and the genes that encode the antibodies' antigens. The data will be made freely available at http://discover.nci.nih.gov/abminer.

Antibodies, Monoclonal↗

PubMed2006

Automated reprocessing pipeline for searching heterogeneous mass spectrometric data of the HUPO Brain Proteome Project pilot phase.

The newly available techniques for sensitive proteome analysis and the resulting amount of data require a new bioinformatics focus on automatic methods for spectrum reprocessing and peptide/protein validation. Manual validation of results in such studies is not feasible and objective enough for quality relevant interpretation. The necessity for tools enabling an automatic quality control is, therefore, important to produce reliable and comparable data in such big consortia as the Human Proteome Organization Brain Proteome Project. Standards and well-defined processing pipelines are important for these consortia. We show a way for choosing the right database model, through collecting data, processing these with a decoy database and end up with a quality controlled protein list merged from several search engines, including a known false-positive rate.

Algorithms↗

PubMedDate not supplied

RECAP--retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry.

The use of combinatorial chemistry for the generation of new lead molecules is now a well established strategy in the drug discovery process. Central to the use of combinatorial chemistry is the design and availability of high quality building blocks which are likely to afford hits from the libraries that they generate. Herein we describe "RECAP" (Retrosynthetic Combinatorial Analysis Procedure), a new computational technique designed to address this building block issue. RECAP electronically fragments molecules based on chemical knowledge. When applied to databases of biologically active molecules this allows the identification of building block fragments rich in biologically recognized elements and privileged motifs and structures. This allows the design of building blocks and the synthesis of libraries rich in biological motifs. Application of RECAP to the Derwent World Drug Index (WDI) and the molecular fragments/ building blocks that this generates are discussed. We also describe a WDI fragment knowledge base which we have built which stores the drug motifs and mention its potential application in structure based drug design programs.

Artificial Intelligence↗

PubMed2000

Epitope scanning using virtual matrix-based algorithms.

Protein sequence and expression databases (transcriptomes) contain the information required to identify epitopes capable of generating protective immune responses in humans. A key event in the initiation of an immune response against disease is the presentation of antigenic peptide epitopes to T cells by human leukocyte antigen (HLA) molecules. Computational filtering tools that allow the prediction of HLA/epitope interaction can be applied to sequence databases to select for candidate epitopes, thus minimising the subsequent amount of laboratory work. Here, the basic principles of epitope prediction and a summary of the available prediction approaches are presented, with a particular emphasis on the use of algorithms based on virtual HLA-II quantitative matrices, capable of predicting promiscuous HLA-II ligands.

Algorithms↗

PubMed2002

Genomics of phytopathogenic fungi and the development of bioinformatic resources.

Genomic resources available to researchers studying phytopathogenic fungi are limited. Here, we briefly review the genomic and bioinformatic resources available and the current status of fungal genomics. We also describe a relational database containing sequences of expressed sequence tags (ESTs) from three phytopathogenic fungi, Blumeria graminis, Magnaporthe grisea, and Mycosphaerella graminicola, and the methods and underlying principles required for its construction. The database contains significant annotation for each EST sequence and is accessible at http://cogeme.ex.ac.uk. An easy-to-use interface allows the user to identify gene sequences by using simple text queries or homology searches. New querying functions and large sequence sets from a variety of phytopathogenic species will be incorporated in due course.

Cladosporium↗

PubMed2005

Identifying remote protein homologs by network propagation.

Perhaps the most widely used applications of bioinformatics are tools such as psi-blast for searching sequence databases. We describe a recently developed protein database search algorithm called rankprop. rankprop relies upon a precomputed network of pairwise protein similarities. The algorithm performs a diffusion operation from a specified query protein across the protein similarity network. The resulting activation scores, assigned to each database protein, encode information about the global structure of the protein similarity network. This type of algorithm has a rich history in associationist psychology, artificial intelligence and web search. We describe the rankprop algorithm and its relatives, and we provide evidence that the algorithm successfully improves upon the rankings produced by psi-blast.

Algorithms↗

PubMed2002

Cluster analysis of an extensive human breast cancer cell line protein expression map database.

In the current study, the protein expression maps (PEMs) of 26 breast cancer cell lines and three cell lines derived from normal breast or benign disease tissue were visualised by high resolution two-dimensional gel electrophoresis. Analysis of this data was performed with ChiClust and ChiMap, two analytical bioinformatics tools that are described here. These tools are designed to facilitate recognition of specific patterns shared by two or more (a series) PEMs. Both tools use PEMs that were matched by an image analysis program and locally written programs to create a match table that is saved in an object relational database. The ChiClust tool uses clustering and subclustering methods to extract statistically significant protein expression patterns from a large series of PEMs. The ChiMap tool calculates a differential value (either as percentage change or a fold change) and represents these graphically. All such differentials or just those identified using ChiClust can be submitted to ChiMap. These methods are not dependent on any particular commercial image analysis program, and the whole software package gives an integrated procedure for the comparison and analysis of a series of PEMs. The ChiClust tool was used here to order the breast cell lines into groups according to biological characteristics including morphology in vitro and tumour forming ability in vivo. ChiMap was then used to highlight eight major protein feature-changes detected between breast cancer cell lines that either do or do not proliferate in nude mice. Mass spectrometry was used to identify the proteins. The possible role of these proteins in cancer is discussed.

Algorithms↗

PubMed2001

Multi-query sequence BLAST output examination with MuSeqBox.

SUMMARY: MuSeqBox is a program to parse BLAST output and store attributes of BLAST hits in tabular form. The user can apply a number of selection criteria to filter out hits with particular attributes. MuSeqBox provides a powerful annotation tool for large sets of query sequences that are simultaneously compared against a database with any of the standard stand-alone or network-client BLAST programs. We discuss such application to the problem of annotation and analysis of EST collections. AVAILABILITY: The program was written in standard C++ and is freely available to noncommercial users by request from the authors. The program is also available over the web at http://bioinformatics.iastate.edu/bioinformatics2go/mb/MuSeqBox.html.

Alternative Splicing↗

PubMed2006

Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules.

MOTIVATION: Various computational methods have been proposed to tackle the problem of predicting the peptide binding ability for a specific MHC molecule. These methods are based on known binding peptide sequences. However, current available peptide databases do not have very abundant amounts of examples and are highly redundant. Existing studies show that MHC molecules can be classified into supertypes in terms of peptide-binding specificities. Therefore, we first give a method for reducing the redundancy in a given dataset based on information entropy, then present a novel approach for prediction by learning a predictive model from a dataset of binders for not only the molecule of interest but also for other MHC molecules. RESULTS: We experimented on the HLA-A family with the binding nonamers of A1 supertype (HLA-A*0101, A*2601, A*2902, A*3002), A2 supertype (A*0201, A*0202, A*0203, A*0206, A*6802), A3 supertype (A*0301, A*1101, A*3101, A*3301, A*6801) and A24 supertype (A*2301 and A*2402), whose data were collected from six publicly available peptide databases and two private sources. The results show that our approach significantly improves the prediction accuracy of peptides that bind a specific HLA molecule when we combine binding data of HLA molecules in the same supertype. Our approach can thus be used to help find new binders for MHC molecules.

Algorithms↗

PubMed2002

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database.

RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.

Amino Acid Sequence↗

PubMed2005

Conservation of gene co-regulation between two prokaryotes: Bacillus subtilis and Escherichia coli.

We measured conservation of gene co-regulation between two distantly related prokaryotes, B. subtilis and E. coli. The co-regulation between genes was extracted from knowledge of regulation of genes stored in databases. For B. subtilis operons, we obtained the data set from ODB which we have developed and, for the regulons, we used DBTBS. For E. coli data set, we used known regulons derived from RegulonDB. We obtained a reliable data set of co-regulated genes in B. subtilis and E. coli. About 60-80 % of gene pairs conserved co-regulation relationships, so co-regulation between genes are highly conserved even between distantly related species. To measure the functional relationship between these conserved genes, we used KEGG PATHWAY and COG. When two co-regulated genes are in the same biological pathway in KEGG or share the same functional category in COG, we assume that they have the same function. As a result, we also found that many conserved co-regulated gene pairs share the same functions. These observations would help to predict gene co-regulation and protein functions.

Bacillus subtilis↗

PubMed2000

Classification of transmembrane protein families in the Caenorhabditis elegans genome and identification of human orthologs.

The complete genome sequence of the nematode Caenorhabditis elegans provides an excellent basis for studying the distribution and evolution of protein families in higher eukaryotes. Three fundamental questions are as follows: How many paralog clusters exist in one species, how many of these are shared with other species, and how many proteins can be assigned a functional counterpart in other species? We have addressed these questions in a detailed study of predicted membrane proteins in C. elegans and their mammalian homologs. All worm proteins predicted to contain at least two transmembrane segments were clustered on the basis of sequence similarity. This resulted in 189 groups with two or more sequences, containing, in total, 2647 worm proteins. Hidden Markov models (HMMs) were created for each family, and were used to retrieve mammalian homologs from the SWISSPROT, TREMBL, and VTS databases. About one-half of these clusters had mammalian homologs. Putative worm-mammalian orthologs were extracted by use of nine different phylogenetic methods and BLAST. Eight clusters initially thought to be worm-specific were assigned mammalian homologs after searching EST and genomic sequences. A compilation of 174 orthology assignments made with high confidence is presented.

Amino Acid Sequence↗

PubMed2005

Differential regulation of the IL-10 gene in Th1 and Th2 T cells.

Interleukin-10 (IL-10), an immunoregulatory cytokine, modulates the function of various immune and nonimmune cells, yet little information is available on the molecular mechanism of transcriptional regulation at the chromatin level. During T cell differentiation from naive T cells into Th1 and Th2 cells, the expression of IL-10 in Th1 cells slowly disappears, whereas Th2 cells produce more IL-10. We examined the chromatin structural changes associated with IL-10 gene transcription by naive and differentiated murine Th1 and Th2 cells. Naive T cells lack DNase I hypersensitivity (HS) sites in the vicinity of the IL-10 gene, whereas differentiated T cells display a strong 3' constitutive HS site as well as several inducible sites. In committed Th1 cells, the mechanism of IL-10 gene silencing is associated with a closed chromatin structure, the lack of an HS site at the promoter region, and the development of repressive histone modification near the IL-10 promoter and introns 3 and 4. We confirm that the majority of HS sites coincide with conserved noncoding sequences (CNSs) identified by comparative genomic sequence alignment between human and mouse genomes. Potential transcription factor binding sites were located by comparing CNSs with the TRANSFAC database. Predicted in vivo binding of specific factors on the CNS locus were confirmed by chromatin immunoprecipitation assays. Our results suggest that the combination of HS site and comparative genomic approaches allows identification of regulatory elements involved in differential IL-10 gene expression between Th1 and Th2 cells during T cell differentiation.

Animals↗

PubMed2006

2005 Human Genome Variation Society Scientific Meeting.

The Annual Scientific Meeting of the Human Genome Variation Society (HGVS) was held on 25 October 2005 in Salt Lake City, Utah. There were four sessions covering topics of interest to members of the HGVS, including mutations and phenotypes, gene variation and disease, methodological approaches, and mutation databases. At this year's annual meeting there was an emphasis on the inclusion of phenotypic information into genomic variation databases. The addition of this information will require the coordinated effort of many individuals from a variety of organizations to ensure that databases will be searchable and meaningful in this effort to combine genomic information, functional data associated with variation, epidemiological data (including environmental exposure), and phenotypic information (especially phenotypes associated with disease). The human genome era is moving into a new phase, and these talks are representative of the new directions in which the study of human DNA variation is going in this exciting area of research.

Computational Biology↗

PubMed2004

GenePaint.org: an atlas of gene expression patterns in the mouse embryo.

High-throughput instruments were recently developed to determine gene expression patterns on tissue sections by RNA in situ hybridization. The resulting images of gene expression patterns, chiefly of E14.5 mouse embryos, are accessible to the public at http://www.genepaint.org. This relational database is searchable for gene identifiers and RNA probe sequences. Moreover, patterns and intensity of expression in approximately 100 different embryonic tissues are annotated and can be searched using a standardized catalog of anatomical structures. A virtual microscope tool, the Zoom Image Server, was implemented in GenePaint.org and permits interactive zooming and panning across approximately 15,000 high-resolution images.

Animals↗

PubMed2005

Bioinformatic "Harvester": a search engine for genome-wide human, mouse, and rat protein resources.

Harvester is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. The Harvester search engine works similar to Google, offering genome-wide ranked results at very high speed. Here we describe how to use this bioinformatic tool along with selected examples.

Animals↗