Super natural II -a database of natural products

Natural products play a significant role in drug discovery and development. Many topological pharmacophore patterns are common between natural products and commercial drugs. A better understanding of the specific physicochemical and structural features of natural products is important for corresponding drug development. Several encyclopedias of natural compounds have been composed, but the information remains scattered or not freely available. The first version of the Supernatural database containing ∼ 50,000 compounds was published in 2006 to face these challenges. Here we present a new, updated and expanded version of natural product database, Super Natural II (http://bioinformatics.charite.de/supernatural), comprising ∼ 326,000 molecules. It provides all corresponding 2D structures, the most important structural and physicochemical properties, the predicted toxicity class for ∼ 170,000 compounds and the vendor information for the vast majority of compounds. The new version allows a template-based search for similar compounds as well as a search for compound names, vendors, specific physical properties or any substructures. Super Natural II also provides information about the pathways associated with synthesis and degradation of the natural products, as well as their mechanism of action with respect to structurally similar drugs and their target proteins

Choosing the right path: enhancement of biologically relevant sets of genes or proteins using pathway structure

A method is proposed that finds enriched pathways relevant to a studied condition, using molecular and network data

Identification of a novel benzimidazole pyrazolone scaffold that inhibits KDM4 lysine demethylases and reduces proliferation of prostate cancer cells

Human lysine demethylase (KDM) enzymes (KDM1-7) constitute an emerging class of therapeutic targets, with activities that support growth and development of metastatic disease. By interacting with and co-activating the androgen receptor, the KDM4 subfamily (KDM4A-E) promotes aggressive phenotypes of prostate cancer (PCa). Knockdown of KDM4 expression or inhibition of KDM4 enzyme activity reduces the proliferation of PCa cell lines and highlights inhibition of lysine demethylation as a possible therapeutic method for PCa treatment. To address this possibility, we screened the ChemBioNet small molecule library for inhibitors of the human KDM4E isoform and identified several compounds with IC50 values in the low micromolar range. Two hits, validated as active by an orthogonal enzyme-linked immunosorbent assay, displayed moderate selectivity toward the KDM4 subfamily and exhibited antiproliferative effects in cellular models of PCa. These compounds were further characterized by their ability to maintain the transcriptionally silent histone H3 tri-methyl K9 epigenetic mark at subcytotoxic concentrations. Taken together, these efforts identify and validate a hydroxyquinoline scaffold and a novel benzimidazole pyrazolone scaffold as tractable for entry into hit-to-lead chemical optimization campaigns

Periodic points in random substitution subshifts

We study various aspects of periodic points for random substitution subshifts. In order to do so, we introduce a new property for random substitutions called the disjoint images condition. We provide a procedure for determining the property for compatible random substitutions—random substitutions for which a well-defined abelianisation exists. We find some simple necessary criteria for primitive, compatible random substitutions to admit periodic points in their subshifts. In the case that the random substitution further has disjoint images and is of constant length, we provide a stronger criterion. A method is outlined for enumerating periodic points of any specified length in a random substitution subshift

Genetic and environmental pathways to complex diseases

<p>Abstract</p> <p>Background</p> <p>Pathogenesis of complex diseases involves the integration of genetic and environmental factors over time, making it particularly difficult to tease apart relationships between phenotype, genotype, and environmental factors using traditional experimental approaches.</p> <p>Results</p> <p>Using gene-centered databases, we have developed a network of complex diseases and environmental factors through the identification of key molecular pathways associated with both genetic and environmental contributions. Comparison with known chemical disease relationships and analysis of transcriptional regulation from gene expression datasets for several environmental factors and phenotypes clustered in a metabolic syndrome and neuropsychiatric subnetwork supports our network hypotheses. This analysis identifies natural and synthetic retinoids, antipsychotic medications, Omega 3 fatty acids, and pyrethroid pesticides as potential environmental modulators of metabolic syndrome phenotypes through PPAR and adipocytokine signaling and organophosphate pesticides as potential environmental modulators of neuropsychiatric phenotypes.</p> <p>Conclusion</p> <p>Identification of key regulatory pathways that integrate genetic and environmental modulators define disease associated targets that will allow for efficient screening of large numbers of environmental factors, screening that could set priorities for further research and guide public health decisions.</p

Wt1 haploinsufficiency induces browning of epididymal fat and alleviates metabolic dysfunction in mice on high-fat diet

Aims/hypothesis: Despite a similar fat storing function, visceral (infra-abdominal) white adipose tissue (WAT) is detrimental, whereas subcutaneous WAT is considered to protect against metabolic disease. Recent findings indicate that thermogenic genes, expressed in brown adipose tissue (BAT), can be induced primarily in subcutaneous WAT. Here, we investigate the hypothesis that the Wilms tumour gene product (WT1), which is expressed in intra-abdominal WAT but not in subcutaneous WAT and BAT, suppresses a thennogenic program in white fat cells. Methods: Heterozygous Wt1 knockout mice and their wild-type littermates were examined in terms of thermogenic and adipocyte-selective gene expression. Glucose tolerance and hepatic lipid accumulation in these mice were assessed under normal chow and high-fat diet conditions. Pre-adipocytes isolated from the stromal vascular fraction of BAT were transduced with Wt1-expressing retrovinis, induced to differentiate and analysed for the expression of thermogenic and adipocyte-selective genes. Results: Expression of the thermogenic genes Cpt1b and Tmem26 was enhanced and transcript levels of Ucp1 were on average more than tenfold higher in epididymal WAT of heterozygous Wt1 knockout mice compared with wild-type mice. Wt1 heterozygosity reduced epididymal WAT mass, improved whole-body glucose tolerance and alleviated severe hepatic steatosis upon diet-induced obesity in mice. Retroviral expression of WT1 in brown pre-adipocytes, which lack endogenous WT1, reduced mRNA levels of Ucp1, Ppargc1a, Cidea, Prdm16 and Cptlb upon in vitro differentiation by 60-90%. WT1 knockdown in epididymal pre-adipocytes significantly lowered Aldh1a1 and Zfp423 transcripts, two key suppressors of the thermogenic program. Conversely, Aldh1a1 and Zfp423 mRNA levels were increased approximately five- and threefold, respectively, by retroviral expression of WT1 in brown pre-adipocytes. Conclusion/interpretation: WT1 functions as a white adipocyte determination factor in epididymal WAT by suppressing thermogenic genes. Reducing Wt1 expression in this and other intra-abdominal fat depots may represent a novel treatment strategy in metabolic disease

Characterization of the proneural gene regulatory network during mouse telencephalon development

BACKGROUND: The proneural proteins Mash1 and Ngn2 are key cell autonomous regulators of neurogenesis in the mammalian central nervous system, yet little is known about the molecular pathways regulated by these transcription factors. RESULTS: Here we identify the downstream effectors of proneural genes in the telencephalon using a genomic approach to analyze the transcriptome of mice that are either lacking or overexpressing proneural genes. Novel targets of Ngn2 and/or Mash1 were identified, such as members of the Notch and Wnt pathways, and proteins involved in adhesion and signal transduction. Next, we searched the non-coding sequence surrounding the predicted proneural downstream effector genes for evolutionarily conserved transcription factor binding sites associated with newly defined consensus binding sites for Ngn2 and Mash1. This allowed us to identify potential novel co-factors and co-regulators for proneural proteins, including Creb, Tcf/Lef, Pou-domain containing transcription factors, Sox9, and Mef2a. Finally, a gene regulatory network was delineated using a novel Bayesian-based algorithm that can incorporate information from diverse datasets. CONCLUSION: Together, these data shed light on the molecular pathways regulated by proneural genes and demonstrate that the integration of experimentation with bioinformatics can guide both hypothesis testing and hypothesis generation