[Computational chemistry and bioinformatics: grid computing for protein simulation].
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Computational Biology↗
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Characterization of binding sites of eukaryotic transcription factors.
To explore the nature of eukaryotic transcription factor (TF) binding sites and determine how they differ from surrounding DNA sequences, we examined four features associated with DNA-binding sites: G+C content, pattern complexity, palindromic structure, and Markov sequence ordering. Our analysis of the regulatory motifs obtained from the TRANSFAC database, using yeast intergenic sequences as background, revealed that these four features show variable enrichment in motif sequences. For example, motif sequences were more likely to have palindromic structure than were background sequences. In addition, these features were tightly localized to the regulatory motifs, indicating that they are a property of the motif sequences themselves and are not shared by the general promoter "environment" in which the regulatory motifs reside. By breaking down the motif sequences according to the TF classes to which they bind, more specific associations were identified. Finally, we found that some correlations, such as G+C content enrichment, were species-specific, while others, such as complexity enrichment, were universal across the species examined. The quantitative analysis provided here should increase our understanding of protein-DNA interactions and also help facilitate the discovery of regulatory motifs through bioinformatics.
Animals↗
Analysis and management of HIV peptide microarray experiments.
OBJECTIVES: To develop a tool for then easy and user-friendly management of peptide microarray experiments and for the use of the results of these experiments for the study the immune response against HIV virus infection in clinical samples. METHODS: Applying bioinformatics and statistics for the analysis of data coming from microarray experiments as well as implementing a MIAME (Minimum Information About a Microarray Experiment) compliant database for managing and annotating experiments, results and samples. RESULTS: We present a new tool for managing not only nucleic acid microarray experiments but also protein microarray experiments. From the analysis of experimental data, we can detect different profiles in the reactivity of the sera with different genotypes. CONCLUSIONS: We have developed a new tool for managing microarray data including clinical annotations for the samples as well as the capability of annotating other microarray formats different to those based on nucleic acids. The use of peptide microarrays and bioinformatics analysis opens a new scope for the characterization of the immune response, and analyzing and identifying the humoral response of viruses with different genotypes.
Computational Biology↗
Effects of chromosomal rearrangements on human-chimpanzee molecular evolution.
Many chromosomes are rearranged between humans and chimpanzees while others remain colinear. It was recently observed, based on over 100 genes, that the rates of protein evolution are substantially higher on rearranged than on colinear chromosomes during human-chimpanzee evolution. This finding led to the conclusion, since debated in the literature, that chromosomal rearrangements had played a key role in human-chimpanzee speciation. Here we re-examine this important conclusion by employing larger a data set (over 7000 genes), as well as alternative analyses. We show that the higher rates of protein evolution on rearranged chromosomes observed in the earlier study are not reproduced by our survey of the larger data set. We further show that the conclusion of the earlier study is likely confounded by two factors introduced by the relatively limited sample size: (1) nonuniform distribution of genes in the genome, and (2) stochastic noise in substitution rates inherent to short lineages such as the human-chimpanzee lineage. Our results offer a general cautionary note on the importance of controlling for hidden factors in studies involving bioinformatic surveys.
Animals↗
Predicting interactions in protein networks by completing defective cliques.
UNLABELLED: Datasets obtained by large-scale, high-throughput methods for detecting protein-protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving the quality of these datasets by predicting missed protein-protein interactions, using only the topology of the protein interaction network observed by the large-scale experiment. The central idea of the method is to search the protein interaction network for defective cliques (nearly complete complexes of pairwise interacting proteins), and predict the interactions that complete them. We formulate an algorithm for applying this method to large-scale networks, and show that in practice it is efficient and has good predictive performance. More information can be found on our website http://topnet.gersteinlab.org/clique/ CONTACT: Mark.Gerstein@yale.edu SUPPLEMENTARY INFORMATION: Supplementary Materials are available at Bioinformatics online.
Algorithms↗
Prioritizing the human genome: knowledge management for drug discovery.
This review covers recent methods to create a manageable subset of drug targets for development by prioritizing novel genes from the Human Genome Project. The ability to organize genomic data into a distinct set of drug discovery assets can be viewed as a form of knowledge management. While bioinformatics systems have been built to manage genomics-based data, the central theme in creating any bioinformatics infrastructure should be organization-specific knowledge management.
Animals↗
The RCSB Protein Data Bank: a redesigned query system and relational database based on the mmCIF schema.
The Protein Data Bank (PDB) is the central worldwide repository for three-dimensional (3D) structure data of biological macromolecules. The Research Collaboratory for Structural Bioinformatics (RCSB) has completely redesigned its resource for the distribution and query of 3D structure data. The re-engineered site is currently in public beta test at http://pdbbeta.rcsb.org. The new site expands the functionality of the existing site by providing structure data in greater detail and uniformity, improved query and enhanced analysis tools. A new key feature is the integration and searchability of data from over 20 other sources covering genomic, proteomic and disease relationships. The current capabilities of the re-engineered site, which will become the RCSB production site at http://www.pdb.org in late 2005, are described.
Databases, Protein↗
IPD--the Immuno Polymorphism Database.
The Immuno Polymorphism Database (IPD) (http://www.ebi.ac.uk/ipd/) is a set of specialist databases related to the study of polymorphic genes in the immune system. IPD currently consists of four databases: IPD-KIR, contains the allelic sequences of Killer-cell Immunoglobulin-like Receptors; IPD-MHC, a database of sequences of the Major Histocompatibility Complex of different species; IPD-HPA, alloantigens expressed only on platelets; and IPD-ESTAB, which provides access to the European Searchable Tumour Cell-Line Database, a cell bank of immunologically characterized melanoma cell lines. The IPD project works with specialist groups or nomenclature committees who provide and curate individual sections before they are submitted to IPD for online publication. The IPD project stores all the data in a set of related databases. Those sections with similar data, such as IPD-KIR and IPD-MHC share the same database structure. The sharing of a common database structure makes it easier to implement common tools for data submission and retrieval. The data are currently available online from the website and ftp directory; files will also be made available in different formats to download from the website and ftp server. The data will also be included in SRS, BLAST and FASTA search engines at the European Bioinformatics Institute.
Animals↗
Steady-state transposon mutagenesis in inbred maize.
We implement a novel strategy for harnessing the power of high-copy transposons for functional analysis of the maize genome, and report behavioral features of the Mutator system in a uniform inbred background. The unique UniformMu population and database facilitate high-throughput molecular analysis of Mu-tagged mutants and gene knockouts. Key features of the population include: (i) high mutation frequencies (7% independent seed mutations) and moderation of copy number (approximately 57 total Mu elements; 1-2 MuDR copies per plant) were maintained by continuous back-crossing into a phenotypically uniform inbred background; (ii) a bz1-mum9 marker enabled selection of stable lines (loss of MuDR), inhibiting further transpositions in lines selected for molecular analysis; (iii) build-up of mutation load was prevented by screening Mu-active parents to exclude plants carrying pre-existing seed mutations. To create a database of genomic sequences flanking Mu insertions, selected mutant lines were analyzed by sequencing of MuTAIL PCR clone libraries. These sequences were annotated and clustered to facilitate bioinformatic subtraction of ancestral elements and identification of insertions unique to mutant lines. New insertions targeted low-copy, gene-rich sequences, and in silico mapping revealed a random distribution of insertions over the genome. Our results indicate that Mu populations differ markedly in the occurrence of Mu insertion hotspots and the frequency of suppressible mutations. We suggest that controlled MuDR copy number in UniformMu lines is a key determinant of these differences. The public database (http://uniformmu.org; http://endosperm.info) includes pedigree and phenotypic data for over 2000 independent seed mutants selected from a population of 31 548 F2 lines and integrated with analyses of 34 255 MuTAIL sequences.
Breeding↗
Proteomics of Halophilic archaea.
Halophilic archaea is a member of the Halobacteriacea family, the only family in the Halobacteriales order. Most Halophilic archaea require 1.5M NaCl both to grow and retain the structural integrity of the cells. The proteins of these organisms have thus been adapted to be active and stable in the hypersaline condition. Consequently, the unique properties of these biocatalysts have resulted in several novel applications in industrial processes. Halophilic archaea are also to be useful for bioremediation of hypersaline environment. Proteome data have expended enormously with the significant advance recently achieved in two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). The whole genome sequencing of Halobacterium species NRC-1 was completed and this would also provide tremendous help to analyze the protein mass data from the similar strain Halobacterium salinarum. Proteomics coupled with genomic databases now has become a basic tool to understand or identify the function of genes and proteins. In addition, the bioinformatics approach will facilitate to predict the function of novel proteins of Halophilic archaea. This review will discuss current proteome study of Halophilic archaea and introduce the efficient procedures for screening, predicting, and confirming the function of novel halophilic enzymes.
Amino Acid Sequence↗
Single nucleotide polymorphism in transcriptional regulatory regions and expression of environmentally responsive genes.
Single nucleotide polymorphisms (SNPs) in the human genome are DNA sequence variations that can alter an individual's response to environmental exposure. SNPs in gene coding regions can lead to changes in the biological properties of the encoded protein. In contrast, SNPs in non-coding gene regulatory regions may affect gene expression levels in an allele-specific manner, and these functional polymorphisms represent an important but relatively unexplored class of genetic variation. The main challenge in analyzing these SNPs is a lack of robust computational and experimental methods. Here, we first outline mechanisms by which genetic variation can impact gene regulation, and review recent findings in this area; then, we describe a methodology for bioinformatic discovery and functional analysis of regulatory SNPs in cis-regulatory regions using the assembled human genome sequence and databases on sequence polymorphism and gene expression. Our method integrates SNP and gene databases and uses a set of computer programs that allow us to: (1) select SNPs, from among the >9 million human SNPs in the NCBI dbSNP database, that are similar to cis-regulatory element (RE) consensus sequences; (2) map the selected dbSNP entries to the human genome assembly in order to identify polymorphic REs near gene start sites; (3) prioritize the candidate polymorphic RE containing genes by searching the existing genotype and gene expression data sets. The applicability of this system has been demonstrated through studies on p53 responsive elements and is being extended to additional pathways and environmentally responsive genes.
Databases, Genetic↗
Cloning, molecular characterization, and expression analysis of Copine 8.
Copines are ubiquitously expressed, phospholipid-binding proteins that have been conserved through evolution. In this paper, we report the cloning and molecular characterization of a new member of the Copine family, Copine 8. This gene has been isolated and characterized using a combination of bioinformatic and experimental approaches. Using an algorithm to cluster ESTs (expressed sequence tags) that are available through the public "GoldenPath" database, Copine 8 was initially identified as a gene predominantly expressed in prostate and testis. Cloning and molecular analysis revealed that this gene is expressed in low-levels in most tissues examined. Two different isoforms of this gene have been isolated. Strongest expression of Copine 8 mRNA is seen in the prostate, heart, and brain. Taken together, this data suggest that Copine 8 may have an important role to play in prostate regulation and development.
Alternative Splicing↗
An overview of data models for the analysis of biochemical pathways.
Biochemical pathways such as metabolic, regulatory or signal transduction pathways can be viewed as interconnected processes forming an intricate network of functional and physical interactions between molecular species in the cell. The amount of information available on such pathways for different organisms is increasing very rapidly. This is offering the possibility of performing various analyses on the structure of the full network of pathways for one organism as well as across different organisms, and has therefore generated interest in developing databases for storing and managing this information. Analysing these networks remains far from straightforward owing to the nature of the databases, which are often heterogeneous, incomplete or inconsistent. Pathway analysis is hence a challenging problem in systems biology and in bioinformatics. Various forms of data models have been devised for the analysis of biochemical pathways. This paper presents an overview of the types of models used for this purpose, concentrating on those concerned with the structural aspects of biochemical networks. In particular, the different types of data models found in the literature are classified using a unified framework. In addition, how these models have been used in the analysis of biochemical networks is described. This enables us to underline the strengths and weaknesses of the different approaches, as well as to highlight relevant future research directions.
Cell Physiological Phenomena↗
Bacterial pathogen genomics and vaccines.
Infectious diseases remain a major cause of deaths and disabilities in the world, the majority of which are caused by bacteria. Although immunisation is the most cost effective and efficient means to control microbial diseases, vaccines are not yet available to prevent many major bacterial infections. Examples include dysentery (shigellosis), gonorrhoea, trachoma, gastric ulcers and cancer (Helicobacter pylori). Improved vaccines are needed to combat some diseases for which current vaccines are inadequate. Tuberculosis, for example, remains rampant throughout most countries in the world and represents a global emergency heightened by the pandemic of HIV. The availability of complete genome sequences has dramatically changed the opportunities for developing novel and improved vaccines and facilitated the efficiency and rapidity of their development. Complete genomic databases provide an inclusive catalogue of all potential candidate vaccines for any bacterial pathogen. In conjunction with adjunct technologies, including bioinformatics, random mutagenesis, microarrays, and proteomics, a systematic and comprehensive approach to identifying vaccine discovery can be undertaken. Genomics must be used in conjunction with population biology to ensure that the vaccine can target all pathogenic strains of a species. A proof in principle of the utility of genomics is provided by the recent exploitation of the complete genome sequence of Neisseria meningitidis group B.
Animals↗
Overexpression of a novel imprinted gene, PEG10, in human hepatocellular carcinoma and in regenerating mouse livers.
Many of the promising applications of the microarray technology are pertinent to identifying abnormalities in gene expression that contribute to malignant progression. We developed a bioinformatics tool to identify differentially expressed genes in human hepatocellular carcinoma (HCC). This involved the construction of a liver EST database (http://lestdb.nhri.org.tw) and in silico verification of differentially expressed genes with a human hepatoma microarray database. The stringency of the search was reinforced with a statistical analysis. A novel imprinted gene, paternally expressed 10(PEG10) was identified as having an elevated level of expression in the majority of the HCC samples and was also induced to express during G2/M phase of regenerating mouse liver. Ectopic expression of PEG10 in 293T cells affects cell cycle progression. PEG10 is distributed in the cytosol and associates with the nuclear membrane. This is the first time that an imprinted gene has been found to reexpress in both human HCC and in the regenerating mouse liver. This result indicates that the induction of the paternally imprinted gene may play an important role during liver regeneration or carcinogenesis of the human hepatocyte. Understanding the molecular basis of the abnormal imprinting of PEG10 will shed new light on the process that leads to liver disease.
Animals↗
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↗
Effect of Chang'an decoction on ulcerative colitis by regulating T helper 17 cells and regulatory T cellsRab27 in the p53/high mobility group box 1 pathway.
OBJECTIVE: To explore the effect of Chang'an decoction (, CAD) of ameliorating the immune imbalances in ulcerative colitis (UC) by regulating Rab27 in the P53/high mobility group box 1 pathway. METHODS: The functions and important signaling pathways of the Rab27- and UC-related genes were analyzed viathe use of microarray data from the gene expression omnibus database, gene ontology database, Kyoto encyclopedia of genes and genomes database and gene set enrichment analysis. Dextran sulfate sodium salt-induced colitis mouse model was used to verify the bioinformatics results. Colon length, body weight, and disease activity index were measured. Hematoxylin and eosin staining was applied to validate the histopathology. Tight junction proteins were detected by immunohistochemistry. The proportions of T helper 17 cells (Th17) and regulatory T cells (Treg) in mesenteric lymph nodes were measured viaflow cytometry. Proinflammatory cytokines like interleukin (IL) 17 (IL-17), IL-21 and IL-22 and anti-inflammatory cytokines like transforming growth factor β and IL-10 in the serum and colon of mice were detected by enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction, respectively. The expression levels of high mobility group box 1 (HMGB1), P53 and phospho- P53 (P-P53) in colonic tissues were detected by immunofluorescence and Western blotting. RESULTS: Bioinformatics analysis revealed that compared with normal tissues, the expression of Rab27 was significantly increased in UC tissues. Receiver operating characteristic curve showed that Rab27 has the potential to be used as a biomarker for the diagnosis of disease activity. Enrichment analysis showed that UC and Rab27 were mainly associated with small molecule transport, nutrient metabolism, transmembrane transport and the downstream pathway of P53. According to animal experiments, the expression of Rab27 was increased in UC tissues, which aggravated the colonic pathological damage, activated the expression of HMGB1, and also leaded to the imbalance of Th17 and Treg cells. After CAD intervention, Rab27 overexpression, weight loss, colon shortening, and pathological damage were substantial reduced, the expression of tight junction proteins, zona occludens 1 and Occludin were increased. The effect of CAD at high-dose was more obvious. In addition, CAD upgraded the number of Treg cells and the production of TGF-β and IL-10, while decreasing the number of Th17 cells and the expression of inflammatory cytokines (IL-17, IL-21, and IL-22). Moreover, colon inflammation was alleviated by CAD, as indicated by the regulation of HMGB1 and P-P53 expression. CONCLUSION: The expression of Rab27, HMGB1 and P-P53 could be decreased by CAD, and the balance of Th17 and Treg cells as well as their related cytokines could be regulated by CAD.
Animals↗
ToothPrint, a proteomic database for dental tissues.
Increasing demand exists to disseminate and integrate proteomic data as proteome analysis assumes a commanding role in the postgenome era. Databases on the World Wide Web are an effective means to share information obtained from two-dimensional gels and allied proteomic approaches. Here we report the establishment of ToothPrint, a proteomic database for dental tissues accessed at http://toothprint.otago.ac.nz. Using developing rat enamel as a prototype, ToothPrint provides a variety of functionally relevant data (ligand binding, subcellular localisation, developmental regulation) in addition to protein identification maps. Features designed to enhance usability of the website and simplify its computing requirements are also outlined. Customized for mineralizing tissues, ToothPrint should prove to be an effective bioinformatic resource for investigations of dental biology.
Animals↗