Bioinformatics in studies of SDR and MDR enzymes.
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11-beta-Hydroxysteroid Dehydrogenases↗
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Rat Genome Database (RGD): mapping disease onto the genome.
The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.
Animals↗
Expressed sequence tags from the midgut and an epithelial cell line of Chironomus tentans: annotation, bioinformatic classification of unknown transcripts and analysis of expression levels.
Expressed sequence tags (ESTs) were generated from two Chironomus tentans cDNA libraries, constructed from an embryo epithelial cell line and from larva midgut tissue. 8584 5'-end ESTs were generated and assembled into 3110 tentative unique transcripts, providing the largest contribution of C. tentans sequences to public databases to date. Annotation using Blast gave 1975 (63.5%) transcripts with a significant match in the major gene/protein databases, 1170 with a best match to Anopheles gambiae and 480 to Drosophila melanogaster. 1091 transcripts (35.1%) had no match to any database. Studies of open reading frames suggest that at least 323 of these contain a coding sequence, indicating that a large proportion of the genes in C. tentans belong to previously unknown gene families.
Animals↗
TRAIL: a molecule with multiple receptors and control mechanisms.
Apoptosis research is benefiting from bioinformatic approaches to identify new components of the cell death machinery and novel cell death inducers/receptors. Over the past year, knowledge of the system involving TNF-related apoptosis-inducing ligand (TRAIL) and its receptors has increased via genomic database analysis to include four distinct receptors that interact with a single ligand. Currently, these molecules are of major interest due to their potential roles and application in cancer therapy.
Animals↗
Expressed sequence tags: alternative or complement to whole genome sequences?
Over three million sequences from approximately 200 plant species have been deposited in the publicly available plant expressed sequence tag (EST) sequence databases. Many of the ESTs have been sequenced as an alternative to complete genome sequencing or as a substrate for cDNA array-based expression analyses. This creates a formidable resource from both biodiversity and gene-discovery standpoints. Bioinformatics-based sequence analysis tools have extended the scope of EST analysis into the fields of proteomics, marker development and genome annotation. Although EST collections are certainly no substitute for a whole genome scaffold, this "poor man's genome" resource forms the core foundations for various genome-scale experiments within the as yet unsequenceable plant genomes.
Computational Biology↗
PLATCOM: a Platform for Computational Comparative Genomics.
MOTIVATION: As more whole genome sequences become available, comparing multiple genomes at the sequence level can provide insight into new biological discovery. However, there are significant challenges for genome comparison. The challenge includes requirement for computational resources owing to the large volume of genome data. More importantly, since the choice of genomes to be compared is entirely subjective, there are too many choices for genome comparison. For these reasons, there is pressing need for bioinformatics systems for comparing multiple genomes where users can choose genomes to be compared freely. RESULTS: PLATCOM (Platform for Computational Comparative Genomics) is an integrated system for the comparative analysis of multiple genomes. The system is built on several public databases and a suite of genome analysis applications are provided as exemplary genome data mining tools over these internal databases. Researchers are able to visually investigate genomic sequence similarities, conserved gene neighborhoods, conserved metabolic pathways and putative gene fusion events among a set of selected multiple genomes. AVAILABILITY: http://platcom.informatics.indiana.edu/platcom
Chromosome Mapping↗
Regulation of expression of symbiotic genes in Rhizobium sp. NGR234.
Research in the field of Rhizobium-legume symbiosis faces a new challenge: integrate the wealth of information generated by genomic projects. The goal: apprehend the complexity of the molecular mechanisms involved in symbiotic associations. At the time of writing, the genomes of three micro-symbionts (Bradyrhizobium japonicum, Mesorhizobium loti and Sinorhizobium meliloti) have been sequenced, and two more (those of Rhizobium leguminosarum and Rhizobium etli) will be completed in the near future. Together, completed rhizobial genomes represent already 23,393,822 bp of DNA sequence and 21,797 predicted open reading frames (ORFs). To identify candidate-symbiotic genes in such a broad database, predict their function and dissect the regulatory networks that govern their expression are no simple tasks. One way to confront this problem is to combine different datasets, in particular genetic and transcriptional maps as well as predicted promoters from bioinformatics analyses. Here, we would like to illustrate this type of approach with the analysis of the symbiotic plasmid (pNGR234a) of the broad host-range Rhizobium sp. NGR234.
Gene Expression Regulation, Bacterial↗
Development of software tools at BioInformatics Centre (BIC) at the National University of Singapore (NUS).
There is burgeoning volume of information and data arising from the rapid research and unprecedented progress in molecular biology. This has been particularly affected by the Human Genome Project which is trying to completely sequence three billion nucleotides of the human genome (1),(1a). Other genome sequencing projects are also contributing substantially to this exponential growth in the number of DNA nucleotides and proteins sequenced. The number of journals, reports and research papers and tools required for the analysis of these sequences has also increased. For this the life sciences today needs tools in information technology and computation to prevent degeneration of this data into an inchoate accretion of unconnected facts and figures. The recently formed BioInformatics Centre (BIC) at the National University of Singapore (NUS) provides access to various commonly used computational tools available over the World Wide Web (WWW)--using a uniform interface and easy access. We have also come up with a new database tool. BioKleisli, which allows you to interact with various geographically scattered, heterogeneous, structurally complex and constantly evolving data sources. This paper summarises the importance of network access and database integration to biomedical research and gives a glimpse of current research conducted at BIC.
Animals↗
New goals for the U.S. Human Genome Project: 1998-2003.
The Human Genome Project has successfully completed all the major goals in its current 5-year plan, covering the period 1993-98. A new plan, for 1998-2003, is presented, in which human DNA sequencing will be the major emphasis. An ambitious schedule has been set to complete the full sequence by the end of 2003, 2 years ahead of previous projections. In the course of completing the sequence, a "working draft" of the human sequence will be produced by the end of 2001. The plan also includes goals for sequencing technology development; for studying human genome sequence variation; for developing technology for functional genomics; for completing the sequence of Caenorhabditis elegans and Drosophila melanogaster and starting the mouse genome; for studying the ethical, legal, and social implications of genome research; for bioinformatics and computational studies; and for training of genome scientists.
Animals↗
Wildfire: distributed, Grid-enabled workflow construction and execution.
BACKGROUND: We observe two trends in bioinformatics: (i) analyses are increasing in complexity, often requiring several applications to be run as a workflow; and (ii) multiple CPU clusters and Grids are available to more scientists. The traditional solution to the problem of running workflows across multiple CPUs required programming, often in a scripting language such as perl. Programming places such solutions beyond the reach of many bioinformatics consumers. RESULTS: We present Wildfire, a graphical user interface for constructing and running workflows. Wildfire borrows user interface features from Jemboss and adds a drag-and-drop interface allowing the user to compose EMBOSS (and other) programs into workflows. For execution, Wildfire uses GEL, the underlying workflow execution engine, which can exploit available parallelism on multiple CPU machines including Beowulf-class clusters and Grids. CONCLUSION: Wildfire simplifies the tasks of constructing and executing bioinformatics workflows.
Algorithms↗
PIMWalker: visualising protein interaction networks using the HUPO PSI molecular interaction format.
UNLABELLED: This article reports on PIMWalker, a free and interactive tool for visualising protein interaction networks. PIMWalker handles the unified molecular interaction (MI) format defined by members of the Proteomics Standards Initiative (the PSI MI format), and it is thus directly and easily usable by bench biologists. PIMWalker also comes with a documented, open-source Javatrade mark application programming interface allowing the bioinformatic programmer to easily extend the functions. AVAILABILITY: PIMWalker is available under a free license from http://pim.hybrigenics.com/pimwalker.
Computer Graphics↗
Utility of the Trypanosoma cruzi sequence database for identification of potential vaccine candidates by in silico and in vitro screening.
Glycosylphosphatidylinositol (GPI)-anchored proteins are abundantly expressed in the infective and intracellular stages of Trypanosoma cruzi and are recognized as antigenic targets by both the humoral and cellular arms of the immune system. Previously, we demonstrated the efficacy of genes encoding GPI-anchored proteins in eliciting partially protective immunity to T. cruzi infection and disease, suggesting their utility as vaccine candidates. For the identification of additional vaccine targets, in this study we screened the T. cruzi expressed sequence tag (EST) and genomic sequence survey (GSS) databases. By applying a variety of web-based genome-mining tools to the analysis of approximately 2,500 sequences, we identified 348 (37.6%) EST and 260 (17.4%) GSS sequences encoding novel parasite-specific proteins. Of these, 19 sequences exhibited the characteristics of secreted and/or membrane-associated GPI proteins. Eight of the selected sequences were amplified to obtain genes TcG1, TcG2, TcG3, TcG4, TcG5, TcG6, TcG7, and TcG8 (TcG1-TcG8) which are expressed in different developmental stages of the parasite and conserved in the genome of a variety of T. cruzi strains. Flow cytometry confirmed the expression of the antigens encoded by the cloned genes as surface proteins in trypomastigote and/or amastigote stages of T. cruzi. When delivered as a DNA vaccine, genes TcG1-TcG6 elicited a parasite-specific antibody response in mice. Except for TcG5, antisera to genes TcG1-TcG6 exhibited trypanolytic activity against the trypomastigote forms of T. cruzi, a property known to correlate with the immune control of T. cruzi. Taken together, our results validate the applicability of bioinformatics in genome mining, resulting in the identification of T. cruzi membrane-associated proteins that are potential vaccine candidates.
Animals↗
Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.
INTRODUCTION: Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. METHODS: The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. RESULTS: A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. DISCUSSION: This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. CONCLUSION: This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.
Molecular Docking Simulation↗
Computational prediction and experimental verification of HVA1-like abscisic acid responsive promoters in rice (Oryza sativa).
Abscisic acid (ABA) is one of the central plant hormones, responsible for controlling both maturation and germination in seeds, as well as mediating adaptive responses to desiccation, injury, and pathogen infection in vegetative tissues. Thorough analyses of two barley genes, HVA1 and HVA22, indicate that their response to ABA relies on the interaction of two cis-acting elements in their promoters, an ABA response element (ABRE) and a coupling element (CE). Together, they form an ABA response promoter complex (ABRC). Comparison of promoters of barley HVA1 and it rice orthologue indicates that the structures and sequences of their ABRCs are highly similar. Prediction of ABA responsive genes in the rice genome is then tractable to a bioinformatics approach based on the structures of the well-defined barley ABRCs. Here we describe a model developed based on the consensus, inter-element spacing and orientations of experimentally determined ABREs and CEs. Our search of the rice promoter database for promoters that fit the model has generated a partial list of genes in rice that have a high likelihood of being involved in the ABA signaling network. The ABA inducibility of some of the rice genes identified was validated with quantitative reverse transcription PCR (QPCR). By limiting our input data to known enhancer modules and experimentally derived rules, we have generated a high confidence subset of ABA-regulated genes. The results suggest that the pathways by which cereals respond to biotic and abiotic stresses overlap significantly, and that regulation is not confined to the level transcription. The large fraction of putative regulatory genes carrying HVA1-like enhancer modules in their promoters suggests the ABA signal enters at multiple points into a complex regulatory network that remains largely unmapped.
Abscisic Acid↗
BuchneraBASE: a post-genomic resource for Buchnera sp. APS.
SUMMARY: BuchneraBASE is a bioinformatic research tool for the genome of the symbiotic bacterium Buchnera sp. APS that includes an improved genome annotation, comparative information about related insect symbiont genomes and a complete mapping of metabolic reactions to an Escherichia coli in silico model. The database is designed to accommodate genome-wide post-genomic datasets that are becoming available for this organism. AVAILABILITY: BuchneraBASE is available at http://www.buchnera.org/.
Buchnera↗
The Universal Protein Resource (UniProt).
The ability to store and interconnect all available information on proteins is crucial to modern biological research. Accordingly, the Universal Protein Resource (UniProt) plays an increasingly important role by providing a stable, comprehensive, freely accessible central resource on protein sequences and functional annotation. UniProt is produced by the UniProt Consortium, formed in 2002 by the European Bioinformatics Institute (EBI), the Protein Information Resource (PIR) and the Swiss Institute of Bioinformatics (SIB). The core activities include manual curation of protein sequences assisted by computational analysis, sequence archiving, development of a user-friendly UniProt web site and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of three major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase and the UniProt Reference Clusters. An additional component consisting of metagenomic and environmental sequences has recently been added to UniProt to ensure availability of such sequences in a timely fashion. UniProt is updated and distributed on a bi-weekly basis and can be accessed online for searches or download at http://www.uniprot.org.
Amino Acid Sequence↗
Exploring the treatment of liver cancer with Gehua Hugan Gao based on bioinformatics, network pharmacology, and molecular docking.
Gehua Hugan Gao (GHHGG) is a traditional Chinese medicine paste that is chiefly used to treat liver cancer. However, the potential impact of GHHGG on liver cancer remains unclear. We explored how GHHGG treats liver cancer using bioinformatics, network pharmacology, and molecular docking. Network pharmacology included GHHGG active ingredients, predicted targets, predicted targets for liver cancer, and differential gene collection. A protein-protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and crucial targets were ranked according to their degree values. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of liver cancer targets were followed by survival, differential analysis, and molecular docking. Venn diagrams show 123 predicted GHHGG targets for the treatment of hepatocellular carcinoma (HCC). Enrichment analysis showed that GHHGG treats HCC through multiple targets and pathways. We also found that estrogen receptor 1, cytochrome P450 3A4, cyclin-dependent kinase 4, type IIA topoisomerase, aurora kinase A, and cyclin E1 targets were closely associated with HCC development through survival and differential analyses. Molecular docking confirmed GHHGG's strong affinity for liver cancer targets. This study helps us understand GHHGG ingredients and targets for liver cancer treatment. To a certain extent, the molecular mechanism of GHHGG in the treatment of liver cancer has been elucidated, thus providing a theoretical basis.
Molecular Docking Simulation↗
Comparative analysis of proteins with a mucus-binding domain found exclusively in lactic acid bacteria.
Lactic acid bacteria (LAB) are frequently encountered inhabitants of the human intestinal tract. A protective layer of mucus covers the epithelial cells of the intestine, offering an attachment site for these bacteria. In this study bioinformatics tools were used to identify and characterize proteins containing one type of mucus-binding domain, called MUB, that is postulated to play an important role in the adherence of LAB to this mucus layer. By searching in all protein databases 48 proteins containing at least one of these MUB domains in nine LAB species were identified. These MUB domains varied in size, ranging from approximately 100 to more than 200 residues per domain. Complete MUB domains were found exclusively in LAB. The number of MUB domains present in a single protein varied from 1 to 15. In some cases, orthologous proteins in closely related species contained a different number of domains, indicating that repeats of the domain undergo rapid duplication and deletion. Proteins containing the MUB domain were often encoded by gene clusters that encode multiple extracellular proteins. In addition to one or more copies of the MUB domain, many of these proteins contained other domains that are predicted to be involved in binding to and degradation of extracellular components. These findings strongly suggest that the MUB domain is an LAB-specific functional unit that performs its task in various domain contexts and could fulfil an important role in host-microbe interactions in the gastrointestinal tract.
Amino Acid Sequence↗