BioThesaurus: a web-based thesaurus of protein and gene names

BioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to protein entries in the UniProt Knowledgebase. Currently covering more than two million proteins, BioThesaurus consists of over 2.8 million names extracted from multiple molecular biological databases according to the database cross-references in iProClass. The BioThesaurus web site allows the retrieval of synonymous names of given protein entries and the identification of protein entries sharing the same names. AVAILABILITY: BioThesaurus is accessible for online searching at http://pir.georgetown.edu/iprolink/biothesaurus     

Annotation and query of tissue microarray data using the NCI Thesaurus

Background  

The Stanford Tissue Microarray Database (TMAD) is a repository of data serving a consortium of pathologists and biomedical researchers. The tissue samples in TMAD are annotated with multiple free-text fields, specifying the pathological diagnoses for each sample. These text annotations are not structured according to any ontology, making future integration of this resource with other biological and clinical data difficult.     

A thesaurus of genetic variation for interrogation of repetitive genomic regions

Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.     

Cloning and sequencing of the levansucrase gene from Acetobacter xylinum NCI 1005.

The levansucrase gene (lsxA) was cloned from the genomic DNA of Acetobacter xylinum NCI 1005, and the nucleotide sequence of the lsxA gene (1,293 bp) was determined. The deduced amino acid sequence of the lsxA gene showed 57.4% and 46.2% identity with the levansucrases from Zymomonas mobilis and Erwinia amylovora, respectively, while only 35.2% identity with that from Acetobacter diazotrophicus. The gene product of lsxA (LsxA) that was overproduced in E. coli coded for a polypeptide of molecular mass 47 kDa. The LsxA released glucose and produced polysaccharide from sucrose, the structure of which was analyzed by nuclear magnetic resonance spectroscopy and determined to be a beta-(2,6)-linked polyfructan.     

Mining the NCI antiviral compounds for HIV-1 integrase inhibitors

HIV-1 integrase (IN) is an essential enzyme for effective viral replication and is a validated target for the development of antiretroviral drugs. Currently, there are no approved drugs targeting this enzyme. In this study, we have identified 11 structurally diverse small-molecule inhibitors of IN. These compounds have been selected by mining the moderately active antiviral molecules from a collection of 90,000 compounds screened by the National Cancer Institute (NCI) Antiviral Program. These compounds, which were screened at the NCI during the past 20 years, resulted in approximately 4000 compounds labeled as 'moderately active.' In our study, chalcone 11 shows the most potent activity with an IC(50) of 2+/-1 microM against purified IN in the presence of both Mn(2+) and Mg(2+) as cofactors. Docking simulations using the 11 identified inhibitors as a training set have elucidated two unique binding areas within the active site: the first encompasses the conserved D64-D116-E152 motif, while the other involves the flexible loop region formed by amino acid residues 140-149. The tested inhibitors exhibit favorable interactions with important amino acid residues through van der Waals and H-bonding contacts.     

Integrating Constitutive Gene Expression and Chemoactivity: Mining the NCI60 Anticancer Screen

Studies into the genetic origins of tumor cell chemoactivity pose significant challenges to bioinformatic mining efforts. Connections between measures of gene expression and chemoactivity have the potential to identify clinical biomarkers of compound response, cellular pathways important to efficacy and potential toxicities; all vital to anticancer drug development. An investigation has been conducted that jointly explores tumor-cell constitutive NCI60 gene expression profiles and small-molecule NCI60 growth inhibition chemoactivity profiles, viewed from novel applications of self-organizing maps (SOMs) and pathway-centric analyses of gene expressions, to identify subsets of over- and under-expressed pathway genes that discriminate chemo-sensitive and chemo-insensitive tumor cell types. Linear Discriminant Analysis (LDA) is used to quantify the accuracy of discriminating genes to predict tumor cell chemoactivity. LDA results find 15% higher prediction accuracies, using ∼30% fewer genes, for pathway-derived discriminating genes when compared to genes derived using conventional gene expression-chemoactivity correlations. The proposed pathway-centric data mining procedure was used to derive discriminating genes for ten well-known compounds. Discriminating genes were further evaluated using gene set enrichment analysis (GSEA) to reveal a cellular genetic landscape, comprised of small numbers of key over and under expressed on- and off-target pathway genes, as important for a compound’s tumor cell chemoactivity. Literature-based validations are provided as support for chemo-important pathways derived from this procedure. Qualitatively similar results are found when using gene expression measurements derived from different microarray platforms. The data used in this analysis is available at http://pubchem.ncbi.nlm.nih.gov/and http://www.ncbi.nlm.nih.gov/projects/geo ({"type":"entrez-geo","attrs":{"text":"GPL96","term_id":"96"}}GPL96, {"type":"entrez-geo","attrs":{"text":"GSE32474","term_id":"32474"}}GSE32474).     

Mapping biomedical terminologies using natural language processing tools and UMLS: Mapping the Orphanet thesaurus to the MeSH

BackgroundOrphanet aims to provide rare disease information to healthcare professionals, patients, and their relatives.ObjectiveThe objective of this work is to evaluate two methodologies (Unified Medical Languages Systems [UMLS] and manual Orphanet-ICD-10 link-based mapping & string-based matching) used to map Orphanet thesaurus to the MeSH thesaurus.ResultsOn a corpus of 375 mappings, the string-based matching provides significantly better results than the UMLS and manual Orphanet-ICD-10 link-based mapping.ConclusionString-based matching could be applied to any biomedical terminology in French not yet included into UMLS.     

Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS

MOTIVATION: An early use of gene-expression data coming from microarrays was to discover non-linear multivariate intergene relationships. Pursuing this direction, the motivation for this paper is 2-fold: (1) to discover and elucidate multivariate logical predictive relations among gene expressions in a dataset arising from radiation studies using the NCI 60 Anti-Cancer Drug Screen (ACDS) cell lines; and (2) to demonstrate how these logical relations based on coarse quantization reflect corresponding relations in the continuous data. RESULTS: Using the coefficient of determination, a large number of logical relationships have been discovered among genes in the NCI 60 ACDS cell lines. Moreover, these relationships can be seen directly in the original continuous data, and many are robust relative to the thresholds used to obtain the logical data from the continuous data. A key observation is that a number of intergene relationships appear to be considerably stronger when p53 is functional as compared to when it is not, which is consistent with earlier findings in the literature. AVAILABILITY: The appendix is available at http://gsp.tamu.edu/Publications/supplement.htm CONTACT: edward@ee.tamu.edu.     

Overview of the principles and practice of biodosimetry

The principle of biodosimetry is to utilize changes induced in the individual by ionizing radiation to estimate the dose and, if possible, to predict or reflect the clinically relevant response, i.e., the biological consequences of the dose. Ideally, the changes should be specific for ionizing radiation, and the response should be unaffected by prior medical or physiological variations among subjects, including changes that might be caused by the stress and trauma from a radiation event. There are two basic types of biodosimetry with different and often complementary characteristics: those based on changes in biological parameters such as gene activation or chromosomal abnormalities and those based on physical changes in tissues (detected by techniques such as EPR). In this paper, we consider the applicability of the various techniques for different scenarios: small- and large-scale exposures to levels of radiation that could lead to the acute radiation syndrome and exposures with lower doses that do not need immediate care, but should be followed for evidence of long-term consequences. The development of biodosimetry has been especially stimulated by the needs after a large-scale event where it is essential to have a means to identify those individuals who would benefit from being brought into the medical care system. Analyses of the conventional methods officially recommended for responding to such events indicate that these methods are unlikely to achieve the results needed for timely triage of thousands of victims. Emerging biodosimetric methods can fill this critically important gap.     

Identification of novel telomeric G-quadruplex-targeting chemical scaffolds through screening of three NCI libraries

Thirteen compounds with diverse chemical structures have been identified as selective telomeric G-quadruplex-binding ligands through screening the NCI Diversity Set II, the NCI Natural Products Set II and the NCI Mechanistic Diversity Set libraries containing a total of 2307 members against a human telomeric G-quadruplex using a FRET-based DNA melting assay. These compounds show significant selectivity towards a telomeric G-quadruplex compared to duplex DNA, fall within a molecular weight range of 327-533, and are generally consistent with the Lipinski Rule of Five for drug-likeness. Thus they provide new chemical scaffolds for the development of novel classes of G-quadruplex-targeting agents.     

Overview of vaccines and vaccination

Of the 80-plus known infectious agents pathogenic for humans, there are now more than 30 vaccines against 26 mainly viral and bacterial infections and these greatly minimize subsequent disease and prevent death after exposure to those agents. This article describes the nature of the vaccines, from live attenuated agents to subunits, their efficacy and safety, and the kind of the immune responses generated by those vaccines, which are so effective. To date, all licensed vaccines generate especially specific antibodies, which attach to the infectious agent and therefore can very largely prevent infection. These vaccines have been so effective in developed countries in preventing mortality after a subsequent infection that attempts are being made to develop vaccines against many of the remaining infectious agents. Many of the latter are difficult to manipulate; they can cause persisting infections or show great antigenic variation. A range of new approaches to improve selected immune responses, such as immunization with DNA or chimeric live vectors, viral or bacterial, are under intense scrutiny, as well as genomic analysis of the agent.