Abstract: The increasing number of publicly available biological databases reflects the evolving need for managing and evaluating abundant and complex data in biological, clinical and computational research. Currently there are over 1000 biologically relevant databases in the public domain with varied content and diverse approaches to capturing and presenting data. This review summarizes the comparatively small niche of sophisticated databases and other resources that aim to enhance understanding of chemicals and their biological actions. The databases reviewed include 1 that emphasizes environmental chemicals and 9 that emphasize drugs and small molecules. These databases and their associated resources are incrementally strengthening the expanding field of toxicogenomics-based research by providing centralized sources of manually and computationally curated datasets and highly sophisticated tools for the meta-analysis of continually increasing environmental chemical, drug and small-molecule datasets.

Abstract: BACKGROUND: It is becoming increasingly accepted that a shift is needed from the traditional target-based approach of drug development towards an integrated perspective of drug action in biochemical systems. To make this change possible, the interaction networks connecting drug targets to all components of biological systems must be identified and characterized. RESULTS: We here present an integrative analysis of the interactions between drugs and metabolism by introducing the concept of metabolic drug scope. The metabolic drug scope represents the full set of metabolic compounds and reactions that are potentially affected by a drug. We constructed and analyzed the scopes of all US approved drugs having metabolic targets. Our analysis shows that the distribution of metabolic drug scopes is highly uneven, and that drugs can be classified into several categories based on their scopes. Some of them have small scopes corresponding to localized action, while others have large scopes corresponding to potential large-scale systemic action. These groups are well conserved throughout different topologies of the underlying metabolic network. They can furthermore be associated to specific drug therapeutic properties. CONCLUSION: These findings demonstrate the relevance of metabolic drug scopes to the characterization of drug-metabolism interactions and to understanding the mechanisms of drug action in a system-wide context.

Abstract: The dangers of serious adverse drug reactions (SADRs) are well known to clinicians, pharmacologists, and the lay public. Efforts to elucidate the molecular mechanisms behind SADRs have made significant progress through genetics and gene expression measurements. However, as the field of pharmacology adopts the same novel higher-density measurement modalities that have proven successful in other areas of biology, one wonders whether there can be more ways to benefit from the explosion of data created by these tools. The development of analytic tools and algorithms to interpret these biological data to create tools for medicine is central to the field of translational bioinformatics. In this review we introduce some of the types of SADR predictors that are required, and we discuss several databases that are publicly available for the study of SADRs, ranging from clinical to molecular measurements. We also describe recent examples of how bioinformatics methods coupled with data repositories can advance the science of SADRs.

Abstract: BACKGROUND: A common method for presenting and studying biological interaction networks is visualization. Software tools can enhance our ability to explore network visualizations and improve our understanding of biological systems, particularly when these tools offer analysis capabilities. However, most published network visualizations are static representations that do not support user interaction. RESULTS: JNets was designed as a network visualization tool that incorporates annotation to explore the underlying features of interaction networks. The software is available as an application and a configurable applet that can provide a flexible and dynamic online interface to many types of network data. As a case study, we use JNets to investigate approved drug targets present within the HIV-1 Human protein interaction network. Our software highlights the intricate influence that HIV-1 has on the host immune response. CONCLUSION: JNets is a software tool that allows interaction networks to be visualized and studied remotely, from within a standard web page. Therefore, using this free software, network data can be presented in an enhanced, interactive format. More information about JNets is available at http://www.manchester.ac.uk/bioinformatics/jnets.

Abstract: Understanding the molecular mechanisms underlying synergistic, potentiative and antagonistic effects of drug combinations could facilitate the discovery of novel efficacious combinations and multi-targeted agents. In this article, we describe an extensive investigation of the published literature on drug combinations for which the combination effect has been evaluated by rigorous analysis methods and for which relevant molecular interaction profiles of the drugs involved are available. Analysis of the 117 drug combinations identified reveals general and specific modes of action, and highlights the potential value of molecular interaction profiles in the discovery of novel multicomponent therapies.

Abstract: AIM: The search for molecules whose bioactivities are similar to those of given compounds or to optimize the initial lead compounds from high throughput screening has attracted increasing interest in recent years. Our goal is to provide a publically searchable database of scaffolds out from a large collection of existing chemical molecules. RESULTS: Although a number of in silico methods have emerged to facilitate this process, which has become known as "scaffold hopping" or "molecular hopping", there is an urgent need for a database system to provide such valuable data in the drug design field. Here we have systematically analyzed a collection of commercially available small molecule databases and a bioactive compound database to identify unique scaffolds and we have built a publically searchable database. The analysis of approximately 4,800,000 of these compounds identified 241,824 unique scaffolds, which are stored in a relational database (http://202.127.30.184:8080/db.html). Each entry in the database is associated with a molecular occurrence and includes its distribution of molecular properties, such as molecular weight, logP, hydrogen bond acceptor number, hydrogen bond donor number, rotatable bond number and ring number. More importantly, for scaffolds derived from the bioactive compounds database, it also contains the original compounds and their target information. CONCLUSION: This Web-based database system could help researchers in the fields of medicinal and organic chemistry to design novel molecules with properties similar to the original compounds, but built on novel scaffolds.

Abstract: The purpose of this research was to evaluate the difference between the pharmaceutical phosphate buffers and the gastrointestinal bicarbonates in dissolution of ketoprofen and indomethacin, to illustrate the dependence of buffer differential on biopharmaceutical properties of BCS II weak acids, and to recommend phosphate buffers equivalent to bicarbonates. The intrinsic dissolution rates of ketoprofen and indomethacin were experimentally measured using a rotating disk method at 37 degrees C in USP SIF/FaSSIF and various concentrations of bicarbonates. Theoretical models including an improved reaction plane model and a film model were applied to estimate the surrogate phosphate buffers equivalent to the bicarbonates. Experimental results show that the intrinsic dissolution rates of ketoprofen and indomethacin in USP and FaSSIF phosphate buffers are 1.5-3.0 times that in the 15 mM bicarbonates. Theoretical analysis demonstrates that the buffer differential is largely dependent on the drug pK(a) and second on solubility, and weakly dependent on the drug diffusivity. Further, in accordance with the drug pK(a), solubility and diffusivity, a simple phosphate surrogate was proposed to match an average bicarbonate value (15 mM) of the upper gastrointestinal region. Specifically, phosphate buffers of 13-15 mM and 3-4 mM were recommended for ketoprofen and indomethacin, respectively. For both ketoprofen and indomethacin, the intrinsic dissolution using the phosphate surrogate buffers closely approximated the 15 mM bicarbonate buffer. This work demonstrates the substantial difference between pharmaceutical phosphates and physiological bicarbonates in determining the drug intrinsic dissolution rates of BCS II weak acids, such as ketoprofen and indomethacin. Surrogate phosphates were recommended in order to closely reflect the in vivo dissolution of ketoprofen and indomethacin in gastrointestinal bicarbonates, which has significant implications for defining buffer systems for BCS II weak acids in developing in vitro bioequivalence dissolution methodology.

Abstract: The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.

Abstract: A central focus of clinical proteomics is to search for biomarkers in plasma for diagnostic and therapeutic use. We studied a set of plasma proteins accessed from the Healthy Human Individual's Integrated Plasma Proteome (HIP(2)) database, a larger set of curated human proteins, and a subset of inflammatory proteins, for overlap with sets of known protein biomarkers, drug targets, and secreted proteins. Most inflammatory proteins were found to occur in plasma, and over three times the level of biomarkers were found in inflammatory plasma proteins and their interacting protein neighbors compared to the sets of plasma and curated human proteins. Percentage overlaps with Gene Ontology terms were similar between the curated human set and plasma protein set, yet the set of inflammatory plasma proteins had a distinct ontology-based profile. Most of the major hub proteins within protein-protein interaction networks of tissue-specific sets of inflammatory proteins were found to occur in disease pathways. The present study presents a systematic approach for profiling a plasma subproteome's relationship to both its potential range of clinical application and its overlap with complex disease.

Abstract: The Comparative Toxicogenomics Database (CTD) is a curated database that promotes understanding about the effects of environmental chemicals on human health. Biocurators at CTD manually curate chemical-gene interactions, chemical-disease relationships and gene-disease relationships from the literature. This strategy allows data to be integrated to construct chemical-gene-disease networks. CTD is unique in numerous respects: curation focuses on environmental chemicals; interactions are manually curated; interactions are constructed using controlled vocabularies and hierarchies; additional gene attributes (such as Gene Ontology, taxonomy and KEGG pathways) are integrated; data can be viewed from the perspective of a chemical, gene or disease; results and batch queries can be downloaded and saved; and most importantly, CTD acts as both a knowledgebase (by reporting data) and a discovery tool (by generating novel inferences). Over 116,000 interactions between 3900 chemicals and 13,300 genes have been curated from 270 species, and 5900 gene-disease and 2500 chemical-disease direct relationships have been captured. By integrating these data, 350,000 gene-disease relationships and 77,000 chemical-disease relationships can be inferred. This wealth of chemical-gene-disease information yields testable hypotheses for understanding the effects of environmental chemicals on human health. CTD is freely available at http://ctd.mdibl.org.