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At least 451 records · Page 25Linked to original sources

PubMed2005

Decoding serological response to Candida cell wall immunome into novel diagnostic, prognostic, and therapeutic candidates for systemic candidiasis by proteomic and bioinformatic analyses.

In an effort to bring novel diagnostic and prognostic biomarkers or even potential targets for vaccine design for systemic candidiasis (SC) into the open, a systematic proteomic approach coupled with bioinformatic analysis was used to decode the serological response to Candida wall immunome in SC patients. Serum levels of IgG antibodies against Candida wall-associated proteins (proteins secreted from protoplasts in active wall regeneration, separated by two-dimensional gel electrophoresis, and identified by mass spectrometry) were measured in 45 SC patients, 57 non-SC patients, and 61 healthy subjects by Western blotting. Two-way hierarchical clustering and principal component analysis of their serum anti-Candida wall antibody expression patterns discriminated SC patients from controls and highlighted the heterogeneity of their expression profiles. Multivariate logistic regression models demonstrated that high levels of antibodies against glucan 1,3-beta-glucosidase (Bgl2p) and the anti-wall phosphoglycerate kinase antibody seropositivity were the only independent predictors of SC. Receiver operating characteristic curve analysis revealed no difference between their combined evaluation and measurement of anti-Bgl2p antibodies alone. In a logistic regression model adjusted for known prognostic factors for mortality, SC patients with high anti-Bgl2p antibody levels or a positive anti-wall enolase antibody status, which correlated with each other, had a reduced 2-month risk of death. After controlling for each other, only the seropositivity for anti-wall enolase antibodies was an independent predictor of a lower risk of fatality, supporting that these mediated the protective effect. No association between serum anti-cytoplasmic enolase antibody levels and outcomes was established, suggesting a specific mechanism of enolase processing during wall biogenesis. We conclude that serum anti-Bgl2p antibodies are a novel accurate diagnostic biomarker for SC and that, at high levels, they may provide protection by modulating the anti-wall enolase antibody response. Furthermore serum anti-wall enolase antibodies are a new prognostic indicator for SC and confer protection against it. Bgl2p and wall-associated enolase could be valuable candidates for future vaccine development.

Aged↗

PubMed2007

Domain analysis of fatty acid synthase protein (NP_217040) from Mycobacterium tuberculosis H37Rv--a bioinformatics study.

Different domains of fatty acid synthase (FAS) protein of Mycobacterium tuberculosis H37Rv, involved in mycolic acid synthesis were analyzed using various bioinformatics tools. Based on different database searches (CDD and Pfam), FAS protein of Mycobacterium tuberculosis was grouped into eight domains, five of which showed close similarity with pdb templates (1MLA, 1IQ6A, 2BMOA, and 1J3NA). Based on the PSI blast analysis, 3D structures of only five domains were predicted using MODELLER software, and loop modeling was done for only those regions that were predicted as loops by predict protein server. Compared to the original structure, the loop modeled structure showed a lower DOPE score value for FAS protein. The X-ray determined templates that were used for predicting the 3D structure suggest that, FAS protein has "Malonyl-coenzyme A-Hydratase-Nitrobenzene dioxygenase-3-oxoacyl-(acp) synthase" activity. Accuracy of the prediction of 3D structure of different domains of FAS protein was further validated by Ramachandran plot and PROCHECK (G-value).

Amino Acid Sequence↗

PubMed2025

Elevated circulating IL-8 correlates with poor prognosis in urological cancers: a meta-analysis and bioinformatic validation.

BACKGROUND: Interleukin-8 (IL-8) is a key cytokine that has been implicated in multiple aspects of cancer progression and therapeutic resistance. Elevated levels of circulating IL-8 (cIL-8) have been implicated in adverse clinical outcomes among patients with urological cancers. However, definitive evidence consolidating these observations remains lacking. The present study aims to synthesize the existing research findings to provide a comprehensive, evidence-based reference for clinical practice. METHODS: A systematic literature search was conducted to identify relevant studies that reported on the prognostic impact of cIL-8 levels in urological cancer patients. Hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS) were extracted and pooled to estimate the overall effect. Furthermore, Kaplan-Meier's survival analyses were conducted using RNA-seq data from The Cancer Genome Atlas (TCGA) through the Gene Expression Profiling Interactive Analysis 2 (GEPIA 2) online tool to validate the observed associations. RESULTS: A total of 19 cohorts encompassing 2740 patients from 12 studies were included in the meta-analysis. The findings revealed that elevated cIL-8 levels were significantly associated with inferior OS (HR: 1.86; 95% confidence intervals (CI): 1.72-2.02) and PFS (HR: 1.59; 95%CI: 1.25-2.03) in patients with urological cancers. The consistency and validity of these results were further supported by survival analyses performed using the GEPIA 2 tool. CONCLUSIONS: This study, which is the first meta-analysis to systematically examine the prognostic significance of cIL-8 in urological cancers, supported by bioinformatics validation, confirms that elevated cIL-8 levels serve as a potential biomarker for predicting adverse outcomes. Our findings underscore the importance of targeting IL-8 as a therapeutic strategy to overcome treatment resistance and improve outcomes for urological cancer patients. Further research into IL-8-targeted therapies and their integration into clinical practice is urgently needed to enhance the treatment landscape for urological cancers.

Humans↗

PubMed2002

Bioinformatics: from genome to drug targets.

The complete sequence determination of the human genome marks the start of a new era in biological science, with focus shifting from sequencing to functional mechanisms of gene products. In addition to effects on gene expression, most of the currently used therapeutic drugs either have enzymes or membrane proteins as their molecular targets of action. These membrane proteins include ion channels and transporters of small molecules, and receptors that convey signals from one side of a membrane to the other. Membrane proteins are thus involved in a variety of cellular processes and have a large potential as targets for new drug discovery. However, detailed structural information is still lacking for the majority of membrane proteins since their association with membrane constituents make NMR (nuclear magnetic resonance) spectroscopic and X-ray diffraction determinations difficult. Molecular modelling by biocomputing is a methodological alternative for structural studies of membrane proteins, but has to be based on experimental structural information in addition to computational techniques. A combination of bioinformatics and experimental techniques was used to model membrane proteins from two different classes, secondary transporters of the sodium:neurotransmitter symporter family (SNF transporters), and G-protein coupled receptors (GPCRs). The protein models were used to examine ligand-protein interactions and signalling/transport mechanisms, and to design experimental site-directed mutagenesis studies. Such studies have provided new insight into the detailed molecular mechanisms of two important classes of membrane proteins, which may be of value in the discovery and development of new pharmaceuticals.

Computational Biology↗

PubMed2006

Bioinformatics for study of autoimmunity.

Recent years have witnessed an explosive growth in available biological data pertaining to autoimmunity research. This includes a tremendous quantity of sequence data (biological structures, genetic and physical maps, pathways, etc.) generated by genome and proteome projects plus extensive clinical and epidemiological data. Autoimmunity research stands to greatly benefit from this data so long as appropriate strategies are available to enable full access to and utilization of this data. The quantity and complexity of this biological data necessitates use of advanced bioinformatics strategies for its efficient retrieval, analysis and interpretation. Major progress has been made in development of specialized tools for storage, analysis and modeling of immunological data, and this has led to development of a whole new field know as immunoinformatics. With advances in novel high-throughput immunology technologies immunoinformatics is transforming understanding of how the immune system functions. This paper reviews advances in the field of immunoinformatics pertinent to autoimmunity research including databases, tools in genomics and proteomics, tools for study of B- and T-cell epitopes, integrative approaches, and web servers.

Allergy and Immunology↗

PubMed2004

Use of bioinformatics and PCR in the search for ABC transporter homology among various bacteria.

Bioinformatics databases and search tools are utilised to produce polymerase chain reaction (PCR) primers for the amplification of an ABC transporter gene from the clinically important anaerobe Finegoldia magna. On sequencing, a 450 base pair amplicon showed homology with the amino acid transporter of Enterococcus faecalis. Little sequence data is available for F. magna and the newly isolated DNA could be a useful tool in the identification of this organism in clinical specimens.

ATP-Binding Cassette Transporters↗

PubMed2005

Molecular cloning and bioinformatics analysis of a novel spliced variant of survivin from human breast cancer cells.

Survivin gene and its two alternatively spliced variants, survivin-2 B and survivin- Delta Ex3 gene were cloned from human breast cancer cell lines B-cap37 firstly. A new gene designated as survivin-image (SI) was cloned from above cell lines, which has not been reported yet to clone from any cell lines. It was found that the novel gene 507 bp comprises partial survivin gene (345 bp), partial image gene (155 bp) of eye cancer and other insertion of 7 bp by analyzing with a series of recent bioinformatics software at the level of nucleotide and protein deduced. Predicted 3-D structures of the new molecule showed greatly similar to that of survivin in N-terminal containing BIR by homology modeling. These results suggested SI gene (GenBank accession No.AY830084) might be a novel alternatively spliced isoforms of the survivin gene involved in other functional significances related to tumorigenesis.

Alternative Splicing↗

PubMed2002

In silico approaches to mechanistic and predictive toxicology: an introduction to bioinformatics for toxicologists.

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new skills and new understanding of genome-scale studies in order to take advantage of the rapidly increasing amount of sequence, expression, and structure information in public and private databases. Toxicologists are poised to take advantage of the large public databases in an effort to decipher the molecular basis of toxicity. With the advent of high-throughput sequencing and computational methodologies, expressed sequences can be rapidly detected and quantitated in target tissues by database searching. Novel genes can also be isolated in silico, while their function can be predicted and characterized by virtue of sequence homology to other known proteins. Genomic DNA sequence data can be exploited to predict target genes and their modes of regulation, as well as identify susceptible genotypes based on single nucleotide polymorphism data. In addition, highly parallel gene expression profiling technologies will allow toxicologists to mine large databases of gene expression data to discover molecular biomarkers and other diagnostic and prognostic genes or expression profiles. This review serves to introduce to toxicologists the concepts of in silico biology most relevant to mechanistic and predictive toxicology, while highlighting the applicability of in silico methods using select examples.

Cluster Analysis↗

PubMed2003

Analysis of structure and function of putative surface-exposed proteins encoded in the Streptococcus pneumoniae genome: a bioinformatics-based approach to vaccine and drug design.

Streptococcus pneumoniae is the most common cause of fatal community-acquired pneumonia, middle ear infection, and meningitis. The prevention and treatment of this infection have become a top priority for the medical-scientific community. The present polysaccharide-based vaccine used to immunize susceptible hosts is only approximately 60% effective and is ineffective in children younger than 2 years of age. The new conjugate vaccine, based on the engineered diphtheria toxin coupled to polysaccharide antigens. is approved only for use in children under 2 years of age to treat invasive disease. While penicillin is the drug of choice to treat infections secondary to S. pneumoniae, increasing numbers of bacterial strains are resistant to penicillin as well as to broad spectrum antibiotics such as vancomycin. Thus, there is a need to identify new strategies to prevent and treat diseases caused by to S. pneumoniae. In this article, we summarize the utilization of the recently available S. pneumoniae genomic information in order to identify and characterize novel proteins likely located on the surface of this Gram-positive pathogenic bacterium. Because only a limited number of surface proteins of S. pneumoniae have been characterized to date, this information provides new insights into the pathogenesis of this organism as well as highlights possible avenues for its treatment and/or prevention in the future. The review is divided into two sections. First, we brietly summarize current information about known surface-exposed proteins of S. pneumoniae. This is followed by the illustration of procedures for the identification of new putative surface-exposed proteins. These have signal peptides required for their extra-cytoplasmic transport and/or additional signature sequences. Some of these will be S. pneumoniae virulence factors. The signature sequences we have chosen are those leading to protein binding to choline present on the bacterial surface, attachment to peptidoglycan of the cell wall, or anchoring to lipids of the cytoplasmic membrane. All these signatures are indicative of binding of proteins to the surface of this organism. Secondly, we illustrate the application of bioinformatics and modeling tools to these selected proteins in order to provide information about their likely functions and preliminary three-dimensional structure models. The focal point of the analysis of these proteins, their sequences, and structures is the evaluation of their antigenic properties and possible roles in pathogenicity. The information obtained from the genome analysis will be instrumental in the development of a more effective prophylactic and/or therapeutic agents to prevent and to treat infections due to S. pneumoniae.

Amino Acid Sequence↗

PubMed1998

Collaborative bioinformatics: data warehouses for targeted experimental results.

Current functional bioinformatics approaches are handicapped by the inability to store functional data at all or by a scattering of data across heterogeneous databases that are difficult to link and query. The Cellular Response Database (CRD) (http://LHI5.umbc.edu/crd) is designed to store and retrieve data concerning changes in in vitro cellular functions associated with stimuli, such as cytokines and drugs. The database can store a broad range of data, including protein or mRNA expression, as well as functional cellular data, such as apoptosis or adherence. This unique ability to store heterogeneous data using a single data model will minimize difficulties associated with searching multiple databases. Authors with articles accepted by participating journals are invited to submit data to the CRD. Submission instructions are outlined, along with a review of the CRD's development.

Cells↗

PubMed2000

Wrapping and interoperating bioinformatics resources using CORBA.

Bioinformaticians seeking to provide services to working biologists are faced with the twin problems of distribution and diversity of resources. Bioinformatics databases are distributed around the world and exist in many kinds of storage forms, platforms and access paradigms. To provide adequate services to biologists, these distributed and diverse resources have to interoperate seamlessly within single applications. The Common Object Request Broker Architecture (CORBA) offers one technical solution to these problems. The key component of CORBA is its use of object orientation as an intermediate form to translate between different representations. This paper concentrates on an explanation of object orientation and how it can be used to overcome the problems of distribution and diversity by describing the interfaces between objects.

Amino Acid Sequence↗

PubMed2000

Phylogenetic--evolutionary approaches to bioinformatics.

Phylogenies of organisms are essential to investigating a range of evolutionary questions of interest to researchers in the field of bioinformatics. Phylogenies not only help to define how to study many evolutionary questions, they must also be taken into account when conducting statistical analyses. Here it is shown how phylogenies can be used to investigate variability along the sites of a gene, reconstruct ancestral states of ancient genes and proteins, identify and characterise events of parallel and convergent evolution, find events of gene duplication, analyse predictions from molecular clocks, seek evidence for correlated changes among different parts of the same gene or genome, and test theories of molecular evolution. A table of statistical and phylogenetic methods is presented.

Animals↗

PubMed2001

On the parallelisation of bioinformatics applications.

This paper surveys the computational strategies followed to parallelise the most used software in the bioinformatics arena. The studied algorithms are computationally expensive and their computational patterns range from regular, such as database-searching applications, to very irregularly structured patterns (phylogenetic trees). Fine- and coarse-grained parallel strategies are discussed for these very diverse sets of applications. This overview outlines computational issues related to parallelism, physical machine models, parallel programming approaches and scheduling strategies for a broad range of computer architectures. In particular, it deals with shared, distributed and shared/distributed memory architectures.

Algorithms↗

PubMed2002

Application of in silico positional cloning and bioinformatic mutation analysis to the study of eye diseases.

A vast amount of DNA and protein sequence is now available and a plethora of programs have been developed to analyse the data. The bewildering variety of analyses that can be performed via the World-Wide Web can deter researchers from applying bioinformatics to augment their traditional genetic research. Focusing on the inherited eye diseases, this paper provides a guide to the appropriate software required for identification of candidate genes through to the detection and analysis of mutations.

Chromosome Mapping↗

PubMed2002

Emerging bioinformatics for the metabolome.

Metabolic profiling applied to functional genomics (metabolomics) is in an early stage of development. Here, the technologies used for metabolite profiling are briefly covered, illustrated by a few pioneering studies. Issues related to bioinformatics, namely data analysis, visualisation and archival, are the main focus of this review. Arguably there is already a need for databases containing metabolite profiles specific for a single organism, and a generic repository containing all metabolite profiling results, regardless of species. Data analyses and visualisations that combine the biological context with chemistry details are suggested as being the most promising.

Animals↗

PubMed2002

Conceptual data modelling for bioinformatics.

Current research in the biosciences depends heavily on the effective exploitation of huge amounts of data. These are in disparate formats, remotely dispersed, and based on the different vocabularies of various disciplines. Furthermore, data are often stored or distributed using formats that leave implicit many important features relating to the structure and semantics of the data. Conceptual data modelling involves the development of implementation-independent models that capture and make explicit the principal structural properties of data. Entities such as a biopolymer or a reaction, and their relations, eg catalyses, can be formalised using a conceptual data model. Conceptual models are implementation-independent and can be transformed in systematic ways for implementation using different platforms, eg traditional database management systems. This paper describes the basics of the most widely used conceptual modelling notations, the ER (entity-relationship) model and the class diagrams of the UML (unified modelling language), and illustrates their use through several examples from bioinformatics. In particular, models are presented for protein structures and motifs, and for genomic sequences.

Computational Biology↗

PubMed2002

Global computing for bioinformatics.

Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster.

Computational Biology↗

PubMed2003

Signal transduction-related bioinformatics services.

Signal transduction pathways are crucial for the regulation of a very wide variety of cellular functions ranging, for example, from translation to intercellular communication, and from metabolism to apoptosis. Protein kinases and phosphatases, together with their binding partners, are key players in these cascades. They also form a substantial part of the genes in genomes and proteins in proteomes in all animals. Signalling can be studied in many different levels and ways. This has resulted in large body of publications and Internet services. This paper describes open-access databases and software aiming at presenting the kind of data available and how to perform bioinformatics analyses.

Computational Biology↗