Abstract: Allosteric modulators are ligands for proteins that exert their effects via a different binding site than the natural (orthosteric) ligand site and hence form a conceptually distinct class of ligands for a target of interest. Here, the physicochemical and structural features of a large set of allosteric and non-allosteric ligands from the ChEMBL database of bioactive molecules are analyzed. In general allosteric modulators are relatively smaller, more lipophilic and more rigid compounds, though large differences exist between different targets and target classes. Furthermore, there are differences in the distribution of targets that bind these allosteric modulators. Allosteric modulators are over-represented in membrane receptors, ligand-gated ion channels and nuclear receptor targets, but are underrepresented in enzymes (primarily proteases and kinases). Moreover, allosteric modulators tend to bind to their targets with a slightly lower potency (5.96 log units versus 6.66 log units, p<0.01). However, this lower absolute affinity is compensated by their lower molecular weight and more lipophilic nature, leading to similar binding efficiency and surface efficiency indices. Subsequently a series of classifier models are trained, initially target class independent models followed by finer-grained target (architecture/functional class) based models using the target hierarchy of the ChEMBL database. Applications of these insights include the selection of likely allosteric modulators from existing compound collections, the design of novel chemical libraries biased towards allosteric regulators and the selection of targets potentially likely to yield allosteric modulators on screening. All data sets used in the paper are available for download.

Abstract: Identifying drug-target interactions has been a key step for drug repositioning, drug discovery and drug design. Since it is expensive to determine the interactions experimentally, computational methods are needed for predicting interactions. In this work, the authors first propose a single-view penalised graph (SPGraph) clustering approach to integrate drug structure and protein sequence data in a structural view. The SPGraph model does clustering on drugs and targets simultaneously such that the known drug-target interactions are best preserved in the clustering results. They then apply the SPGraph to a chemical view with drug response data and gene expression data in NCI-60 cell lines. They further generalise the SPGraph to a multi-view penalised graph (MPGraph) version, which can integrate the structural view and chemical view of the data. In the authors' experiments, they compare their approach with some comparison partners, and the results show that the SPGraph could improve the prediction accuracy in a small scale, and the MPGraph can achieve around 10% improvements for the prediction accuracy. They finally give some new targets for 22 Food and Drug Administration approved drugs for drug repositioning, and some can be supported by other references.

Abstract: One goal of aging research is to find drugs that delay the onset of age-associated disease. Studies in invertebrates, particularly Caenorhabditis elegans, have uncovered numerous genes involved in aging, many conserved in mammals. However, which of these encode proteins suitable for drug targeting is unknown. To investigate this question, we screened a library of compounds with known mammalian pharmacology for compounds that increase C. elegans lifespan. We identified 60 compounds that increase longevity in C. elegans, 33 of which also increased resistance to oxidative stress. Many of these compounds are drugs approved for human use. Enhanced resistance to oxidative stress was associated primarily with compounds that target receptors for biogenic amines, such as dopamine or serotonin. A pharmacological network constructed with these data reveal that lifespan extension and increased stress resistance cluster together in a few pharmacological classes, most involved in intercellular signaling. These studies identify compounds that can now be explored for beneficial effects on aging in mammals, as well as tools that can be used to further investigate the mechanisms underlying aging in C. elegans.

Abstract: The Rv1217c-Rv1218c multidrug efflux system, which belongs to the ATP-binding cassette superfamily, recognizes and actively extrudes a variety of structurally unrelated toxic chemicals and mediates the intrinsic resistance to these antimicrobials in Mycobacterium tuberculosis. The expression of Rv1217c-Rv1218c is controlled by the TetR-like transcriptional regulator Rv1219c, which is encoded by a gene immediately upstream of rv1218c. To elucidate the structural basis of Rv1219c regulation, we have determined the crystal structure of Rv1219c, which reveals a dimeric two-domain molecule with an entirely helical architecture similar to members of the TetR family of transcriptional regulators. The N-terminal domains of the Rv1219c dimer are separated by a large center-to-center distance of 64 A. The C-terminal domain of each protomer possesses a large cavity. Docking of small compounds to Rv1219c suggests that this large cavity forms a multidrug binding pocket, which can accommodate a variety of structurally unrelated antimicrobial agents. The internal wall of the multidrug binding site is surrounded by seven aromatic residues, indicating that drug binding may be governed by aromatic stacking interactions. In addition, fluorescence polarization reveals that Rv1219c binds drugs in the micromolar range.

Abstract: The genomic era has enabled research projects that use approaches including genome-scale screens, microarray analysis, next-generation sequencing, and mass spectrometry-based proteomics to discover genes and proteins involved in biological processes. Such methods generate data sets of gene, transcript, or protein hits that researchers wish to explore to understand their properties and functions and thus their possible roles in biological systems of interest. Recent years have seen a profusion of Internet-based resources to aid this process. This review takes the viewpoint of the curious biologist wishing to explore the properties of protein-coding genes and their products, identified using genome-based technologies. Ten key questions are asked about each hit, addressing functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, interactors, posttranslational modifications, and inhibitors. Answers are provided by presenting the latest publicly available resources, together with methods for hit-specific and data set-wide information retrieval, suited to any genome-based analytical technique and experimental species. The utility of these resources is demonstrated for 20 factors regulating cell proliferation. Results obtained using some of these are discussed in more depth using the p53 tumor suppressor as an example. This flexible and universally applicable approach for characterizing experimental hits helps researchers to maximize the potential of their projects for biological discovery.

Abstract: Gastrointestinal disturbances are a side-effect frequently associated with haematological malignancies due to the intensive cytotoxic treatment given in connection with bone marrow transplantation (BMT). However, intestinal microbiota changes during chemotherapy remain poorly described, probably due to the use of culture-based and low-resolution molecular methods in previous studies. The objective of our study was to apply a next generation DNA sequencing technology to analyse chemotherapy-induced changes in faecal microbiota. We included eight patients with non-Hodgkin's lymphoma undergoing one course of BMT conditioning chemotherapy. We collected a prechemotherapy faecal sample, the day before chemotherapy was initiated, and a postchemotherapy sample, collected 1 week after the initiation of chemotherapy. Total DNA was extracted from faecal samples, denaturing high-performance liquid chromatography based on amplification of the V6 to V8 region of the 16S ribosomal RNA (rRNA) gene, and 454-pyrosequencing of the 16 S rRNA gene, using PCR primers targeting the V5 and V6 hypervariable 16S rRNA gene regions were performed. Raw sequence data were screened, trimmed, and filtered using the QIIME pipeline. We observed a steep reduction in alpha diversity and significant differences in the composition of the intestinal microbiota in response to chemotherapy. Chemotherapy was associated with a drastic drop in Faecalibacterium and accompanied by an increase of Escherichia. The chemotherapy-induced shift in the intestinal microbiota could induce severe side effects in immunocompromised cancer patients. Our study is a first step in identifying patients at risk for gastrointestinal disturbances and to promote strategies to prevent this drastic shift in intestinal microbiota.

Abstract: Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated rcv2 value of 0.84 using three principal components and non-cross-validated r2 value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.

Abstract: A series of Phe-Gly dipeptide-derived piperazinones containing an aromatic urea moiety and a basic amino acid has been synthesized and evaluated as inhibitors of human platelet aggregation induced by the PAR1 agonist SFLLRN and as cytotoxic agents in human cancer cells. The synthetic strategy involves coupling of a protected basic amino acid benzyl amide to 1,2- and 1,2,4-substituted-piperazinone derivatives, through a carbonylmethyl group at the N1-position, followed by formation of an aromatic urea at the exocyclic moiety linked at the C2 position of the piperazine ring and removal of protecting groups. None of the compounds showed activity in the biological evaluation.

Abstract: MOTIVATION: Chemical named entity recognition is used to automatically identify mentions to chemical compounds in text and is the basis for more elaborate information extraction. However, only a small number of applications are freely available to identify such mentions. Particularly challenging and useful is the identification of International Union of Pure and Applied Chemistry (IUPAC) chemical compounds, which due to the complex morphology of IUPAC names requires more advanced techniques than that of brand names. RESULTS: We present CheNER, a tool for automated identification of systematic IUPAC chemical mentions. We evaluated different systems using an established literature corpus to show that CheNER has a superior performance in identifying IUPAC names specifically, and that it makes better use of computational resources. AVAILABILITY AND IMPLEMENTATION: http://metres.udl.cat/index.php/9-download/4-chener, http://chener.bioinfo.cnio.es/

Abstract: The newly emerged Middle East respiratory syndrome coronavirus (MERS-CoV) is becoming another "SARS-like" threat to the world. It has an extremely high death rate ( approximately 50%) as there is no vaccine or efficient therapeutics. The identification of the structures of both the MERS-CoV receptor binding domain (RBD) and its complex with dipeptidyl peptidase 4 (DPP4), raises the hope of alleviating this currently severe situation. In this review, we examined the molecular basis of the RBD-receptor interaction to outline why/how could we use MERS-CoV RBD to develop vaccines and antiviral drugs.