MOTIVATION: The identification of interactions between drugs and target proteins is a key area in genomic drug discovery. Therefore, there is a strong incentive to develop new methods capable of detecting these potential drug-target interactions efficiently. RESULTS: In this article, we characterize four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, and reveal significant correlations between drug structure similarity, target sequence similarity and the drug-target interaction network topology. We then develop new statistical methods to predict unknown drug-target interaction networks from chemical structure and genomic sequence information simultaneously on a large scale. The originality of the proposed method lies in the formalization of the drug-target interaction inference as a supervised learning problem for a bipartite graph, the lack of need for 3D structure information of the target proteins, and in the integration of chemical and genomic spaces into a unified space that we call 'pharmacological space'. In the results, we demonstrate the usefulness of our proposed method for the prediction of the four classes of drug-target interaction networks. Our comprehensively predicted drug-target interaction networks enable us to suggest many potential drug-target interactions and to increase research productivity toward genomic drug discovery. AVAILABILITY: Softwares are available upon request. SUPPLEMENTARY INFORMATION: Datasets and all prediction results are available at http://web.kuicr.kyoto-u.ac.jp/supp/yoshi/drugtarget/.

UNLABELLED: Infectious diseases are a major threat to global public health and prosperity. The causative agents consist of a suite of pathogens, ranging from bacteria to viruses, including fungi, helminthes and protozoa. Although these organisms are extremely varied in their biological structure and interactions with the host, they share similar methods of evading the host immune system. Antigenic variation and drift are mechanisms by which pathogens change their exposed epitopes while maintaining protein function. Accordingly, these traits enable pathogens to establish chronic infections in the host. The varDB database was developed to serve as a central repository of protein and nucleotide sequences as well as associated features (e.g. field isolate data, clinical parameters, etc.) involved in antigenic variation. The data currently contained in varDB were mined from GenBank as well as multiple specialized data repositories (e.g. PlasmoDB, GiardiaDB). Family members and ortholog groups were identified using a hierarchical search strategy, including literature/author-based searches and HMM profiles. Included in the current release are>29,00 sequences from 39 gene families from 25 different pathogens. This resource will enable researchers to compare antigenic variation within and across taxa with the goal of identifying common mechanisms of pathogenicity to assist in the fight against a range of devastating diseases. AVAILABILITY: varDB is freely accessible at http://www.vardb.org/

BACKGROUND: Phage display is widely used in basic research such as the exploration of protein-protein interaction sites and networks, and applied research such as the development of new drugs, vaccines, and diagnostics. It has also become a promising method for epitope mapping. Research on new algorithms that assist and automate phage display based epitope mapping has attracted many groups. Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them. RESULTS: We present MIMOX, a free web tool that helps to map the native epitope of an antibody based on one or more user supplied mimotopes and the antigen structure. MIMOX was coded in Perl using modules from the Bioperl project. It has two sections. In the first section, MIMOX provides a simple interface for ClustalW to align a set of mimotopes. It also provides a simple statistical method to derive the consensus sequence and embeds JalView as a Java applet to view and manage the alignment. In the second section, MIMOX can map a single mimotope or a consensus sequence of a set of mimotopes, on to the corresponding antigen structure and search for all of the clusters of residues that could represent the native epitope. NACCESS is used to evaluate the surface accessibility of the candidate clusters; and Jmol is embedded to view them interactively in their 3D context. Initial case studies show that MIMOX can reproduce mappings from existing tools such as FINDMAP and 3DEX, as well as providing novel, rational results. CONCLUSION: A web-based tool called MIMOX has been developed for phage display based epitope mapping. As a publicly available online service in this area, it is convenient for the community to access, utilize, and evaluate, complementing other existing programs. MIMOX is freely available at http://web.kuicr.kyoto-u.ac.jp/~hjian/mimox.