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At least 91 records · Page 5Linked to original sources
PubMed2006

Global mapping of pharmacological space.

We present the global mapping of pharmacological space by the integration of several vast sources of medicinal chemistry structure-activity relationships (SAR) data. Our comprehensive mapping of pharmacological space enables us to identify confidently the human targets for which chemical tools and drugs have been discovered to date. The integration of SAR data from diverse sources by unique canonical chemical structure, protein sequence and disease indication enables the construction of a ligand-target matrix to explore the global relationships between chemical structure and biological targets. Using the data matrix, we are able to catalog the links between proteins in chemical space as a polypharmacology interaction network. We demonstrate that probabilistic models can be used to predict pharmacology from a large knowledge base. The relationships between proteins, chemical structures and drug-like properties provide a framework for developing a probabilistic approach to drug discovery that can be exploited to increase research productivity.

Computational Biology↗
PubMed2005

Exploring icosahedral virus structures with VIPER.

Virus structures are megadalton nucleoprotein complexes with an exceptional variety of protein-protein and protein-nucleic-acid interactions. Three-dimensional crystal structures of over 70 virus capsids, from more than 20 families and 30 different genera of viruses, have been solved to near-atomic resolution. The enormous amount of information contained in these structures is difficult to access, even for scientists trained in structural biology. Virus Particle Explorer (VIPER) is a web-based catalogue of structural information that describes the icosahedral virus particles. In addition to high-resolution crystal structures, VIPER has expanded to include virus structures obtained by cryo-electron microscopy (EM) techniques. The VIPER database is a powerful resource for virologists, microbiologists, virus crystallographers and EM researchers. This review describes how to use VIPER, using several examples to show the power of this resource for research and educational purposes.

Capsid↗
PubMed2006

Map quest.

Explore the source record for details and available documents.

Databases, Factual↗
PubMed2005

Linking pathway gene expressions to the growth inhibition response from the National Cancer Institute's anticancer screen and drug mechanism of action.

Novel strategies are proposed to quantitatively analyze and relate biological pathways to drug responses using gene expression and small-molecule growth inhibition data (GI(50)) derived from the National Cancer Institute's 60 cancer cells (NCI(60)). We have annotated groups of drug GI(50) responses with pathways defined by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta, and functional categories defined by Gene Ontology (GO), through correlations between pathway gene expression patterns and drug GI(50) profiles. Drug-gene-pathway relationships may then be utilized to find drug targets or target-specific drugs. Significantly correlated pathways and the gene products involved represent interesting targets for further exploration, whereas drugs that are significantly correlated with only certain pathways are more likely to be target specific. Separate pathway clustering finds that pathways engaged in the same biological process tend to have similar drug correlation patterns. The biological and statistical significances of our method are established by comparison to known small-molecule inhibitor-gene target relationships reported in the literature and by standard randomization procedures. The results of our pathway, gene expression and drug-induced growth inhibition associations, can serve as a basis for proposing testable hypotheses about potential anticancer drugs, their targets, and mechanisms of action.

Antineoplastic Agents↗
PubMedDate not supplied

Unraveling the evolutionary radiation of the families of the Zingiberales using morphological and molecular evidence.

The Zingiberales are a tropical group of monocotyledons that includes bananas, gingers, and their relatives. The phylogenetic relationships among the eight families currently recognized are investigated here by using parsimony and maximum likelihood analyses of four character sets: morphological features (1), and sequence data of the (2) chloroplast rbcL gene, (3) chloroplast atpB gene, and (4) nuclear 18S rDNA gene. Outgroups for the analyses include the closely related Commelinaceae + Philydraceae + Haemodoraceae + Pontederiaceae + Hanguanaceae as well as seven more distantly related monocots and paleoherbs. Only slightly different estimates of evolutionary relationships result from the analysis of each character set. The morphological data yield a single fully resolved most-parsimonious tree. None of the molecular datasets alone completely resolves interfamilial relationships. The analyses of the combined molecular dataset provide more resolution than do those of individual genes, and the addition of the morphological data provides a well-supported estimate of phylogenetic relationships: (Musaceae ((Strelitziaceae, Lowiaceae) (Heliconiaceae ((Zingiberaceae, Costaceae) (Cannaceae, Marantaceae))))). Evidence from branch lengths in the parsimony analyses and from the fossil record suggests that the Zingiberales originated in the Early Cretaceous and underwent a rapid radiation in the mid-Cretaceous, by which time most extant family lineages had diverged.

DNA, Plant↗
PubMed2005

Bioinformatics in drug development and assessment.

Bioinformatics is playing an increasingly important role in nearly all aspects of drug discovery, drug assessment, and drug development. This growing importance lies not only in the role that bioinformatics plays in handling large volumes of data, but also in the utility of bioinformatics tools to predict, analyze, or help interpret clinical and preclinical findings. This review focuses on describing and evaluating some of the newer or more important bioinformatics resources (i.e., databases and software) that are of growing importance to understanding or predicting drug metabolism, especially with respect to the absorption, distribution, metabolism, excretion, (ADME), and toxicity (T) of both existing drugs and potential drug leads. Detailed descriptions and critical assessments of a number of potentially useful bioinformatics/cheminformatics databases and predictive ADMET software tools are provided. Additionally, several pharmaceutically important applications of both the databases and software are highlighted. Given the rapid growth in this area and the rapid changes that are taking place, a special emphasis is placed on freely available or Web-accessible resources.

Animals↗
PubMed2003

A computational study of Shewanella oneidensis MR-1: structural prediction and functional inference of hypothetical proteins.

The genomes of many organisms have been sequenced in the last 5 years. Typically about 30% of predicted genes from a newly sequenced genome cannot be given functional assignments using sequence comparison methods. In these situations three-dimensional structural predictions combined with a suite of computational tools can suggest possible functions for these hypothetical proteins. Suggesting functions may allow better interpretation of experimental data (e.g., microarray data and mass spectroscopy data) and help experimentalists design new experiments. In this paper, we focus on three hypothetical proteins of Shewanella oneidensis MR-1 that are potentially related to iron transport/metabolism based on microarray experiments. The threading program PROSPECT was used for protein structural predictions and functional annotation, in conjunction with literature search and other computational tools. Computational tools were used to perform transmembrane domain predictions, coiled coil predictions, signal peptide predictions, sub-cellular localization predictions, motif prediction, and operon structure evaluations. Combined computational results from all tools were used to predict roles for the hypothetical proteins. This method, which uses a suite of computational tools that are freely available to academic users, can be used to annotate hypothetical proteins in general.

ATP-Binding Cassette Transporters↗
PubMed1996

Setting standards for DNA banks: toward a model code of conduct.

As genomic research proliferates, DNA banking will become more common. In research, samples will be banked largely in an effort to find and clone genes that predispose to disease. Commercially oriented banks, those that offer services to families, may also become more common. These entities will hold sensitive information. DNA banking is not yet regulated. We argue here that new laws are not needed at this time to regulate DNA banking. We suggest an approach that relies on a professional code of conduct and draws on principles of disclosure inherent to the process used in obtaining informed consent. In addition to suggesting 12 specific recommendations for the code of conduct, we suggest that items should be included in depositor's agreements. We offer a rationale for our suggestions.

Biological Specimen Banks↗
PubMed2004

Semantic search among heterogeneous biological databases based on gene ontology.

Semantic search is a key issue in integration of heterogeneous biological databases. In this paper, we present a methodology for implementing semantic search in BioDW, an integrated biological data warehouse. Two tables are presented: the DB2GO table to correlate Gene Ontology (GO) annotated entries from BioDW data sources with GO, and the semantic similarity table to record similarity scores derived from any pair of GO terms. Based on the two tables, multifarious ways for semantic search are provided and the corresponding entries in heterogeneous biological databases in semantic terms can be expediently searched.

Database Management Systems↗