Revealing cytotoxic substructures in molecules using deep learning

In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical advances and the ever growing amount of available toxicity data enabled machine learning, especially neural networks, to impact the field of predictive toxicology. In this study, cytotoxicity prediction, one of the earliest handles in drug discovery, is investigated using a deep learning approach trained on a highly consistent in-house data set of over 34,000 compounds with a share of less than 5% of cytotoxic molecules. The model reached a balanced accuracy of over 70%, similar to previously reported studies using Random Forest. Albeit yielding good results, neural networks are often described as a black box lacking deeper mechanistic understanding of the underlying model. To overcome this absence of interpretability, a Deep Taylor Decomposition method is investigated to identify substructures that may be responsible for the cytotoxic effects, the so-called toxicophores. Furthermore, this study introduces cytotoxicity maps which provide a visual structural interpretation of the relevance of these substructures. Using this approach could be helpful in drug development to predict the potential toxicity of a compound as well as to generate new insights into the toxic mechanism. Moreover, it could also help to de-risk and optimize compounds

Interoperable multimedia metadata through similarity-based semantic web service discovery

The increasing availability of multimedia (MM) resources, Web services as well as content, on the Web raises the need to automatically discover and process resources out of distributed repositories. However, the heterogeneity of applied metadata schemas and vocabularies – ranging from XML-based schemas such as MPEG-7 to formal knowledge representation approaches – raises interoperability problems. To enable MM metadata interoperability by means of automated similarity-computation, we propose a hybrid representation approach which combines symbolic MM metadata representations with a grounding in so-called Conceptual Spaces (CS). In that, we enable automatic computation of similarities across distinct metadata vocabularies and schemas in terms of spatial distances in shared CS. Moreover, such a vector-based approach is particularly well suited to represent MM metadata, given that a majority of MM parameters is provided in terms of quantified metrics. To prove the feasibility of our approach, we provide a prototypical implementation facilitating similarity-based discovery of publicly available MM services, aiming at federated MM content retrieval out of heterogeneous repositories

Pharmacological restoration and therapeutic targeting of the B-cell phenotype in classical Hodgkin's lymphoma

Classical Hodgkin's lymphoma (cHL), although originating from B-cells, is characterized by the virtual lack of gene products whose expression constitutes the B-cell phenotype. Epigenetic repression of B-cell-specific genes via promoter hypermethylation and histone deacetylation as well as compromised expression of B-cell-committed transcription factors were previously reported to contribute to the lost B-cell phenotype in cHL. Restoring the B-cell phenotype may not only correct a central malignant property, but render cHL susceptible to clinically established antibody therapies targeting B-cell surface receptors or small compounds interfering with B-cell receptor signaling. We conducted now a high-throughput pharmacological screening based on more than 28,000 compounds in cHL cell lines carrying a CD19 reporter to identify drugs that promote re-expression of the B-cell phenotype. Three chemicals were retrieved that robustly enhanced CD19 transcription. Subsequent chromatin immunoprecipitation-based analyses indicated that action of two of these compounds was associated with lowered levels of the transcriptionally repressive lysine 9-trimethylated histone H3 mark at the CD19 promoter. Moreover, the anti-leukemia agents all-trans retinoic acid and arsenic trioxide (ATO) were found to reconstitute the silenced B-cell transcriptional program and reduce viability of cHL cell lines. When applied in combination with a screening-identified chemical, ATO evoked re-expression of the CD20 antigen, which could be further therapeutically exploited by enabling CD20 antibody-mediated apoptosis of cHL cells. Furthermore, restoration of the B-cell phenotype also rendered cHL cells susceptible to the B-cell Non-Hodgkin's lymphoma-tailored small compound inhibitors Ibrutinib and Idelalisib. In essence, we report here a conceptually novel, re-differentiation-based treatment strategy for cHL

Industry concentration and strategic trade policy in successive oligopoly

We study a policy game between exporting and importing countries in vertically linked industries. In a successive international Cournot oligopoly, we analyse incentives for using tax instruments strategically to shift rents vertically, between exporting and importing countries, and horizontally, between exporting countries. We show that the equilibrium outcome depends crucially on the relative degree of competitiveness in the upstream and downstream parts of the industry. With respect to national welfare, a more competitive upstream industry may benefit an exporting (upstream) country and harm an importing (downstream) country. On the other hand, a more competitive downstream industry may harm exporting countries.Financial support from the Norwegian Research Council, through the PETROPOL research programme, is gratefully acknowledged. The paper has been greatly improved by the suggestions of two anonymous referees. We also thank Hisashi Hokari and Frode Meland for valuable comments and suggestions

High-Throughput Screening for Modulators of CFTR Activity Based on Genetically Engineered Cystic Fibrosis Disease-Specific iPSCs

Organotypic culture systems from disease-specific induced pluripotent stem cells (iPSCs) exhibit obvious advantages compared with immortalized cell lines and primary cell cultures, but implementation of iPSC-based high-throughput (HT) assays is still technically challenging. Here, we demonstrate the development and conduction of an organotypic HT Cl/I exchange assay using cystic fibrosis (CF) disease-specific iPSCs. The introduction of a halide-sensitive YFP variant enabled automated quantitative measurement of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) function in iPSC-derived intestinal epithelia. CFTR function was partially rescued by treatment with VX-770 and VX-809, and seamless gene correction of the p.Phe508del mutation resulted in full restoration of CFTR function. The identification of a series of validated primary hits that improve the function of p.Phe508del CFTR from a library of 42,500 chemical compounds demonstrates that the advantages of complex iPSC-derived culture systems for disease modeling can also be utilized for drug screening in a true HT format

Topical inflammasome inhibition with disulfiram prevents irritant contact dermatitis

BACKGROUND: The pathogenesis of contact dermatitis, a common inflammatory skin disease with limited treatment options, is held to be driven by inflammasome activation induced by allergens and irritants. We here aim to identify inflammasome-targeting treatment strategies for irritant contact dermatitis. METHODS: A high content screen with 41,184 small molecules was performed using fluorescent Apoptosis associated speck-like protein containing a CARD (ASC) speck formation as a readout for inflammasome activation. Hit compounds were validated for inhibition of interleukin (IL)-1β secretion. Of these, the approved thiuramdisulfide derivative disulfiram was selected and tested in a patch test model of irritant contact dermatitis in 25 healthy volunteers. Topical application of disulfiram, mometasone or vehicle was followed by application of sodiumdodecylsulfate (SDS) for 24 h each. Eczema induction was quantified by mexameter and laser speckle imaging. Corneocyte sampling of lesional skin was performed to assess inflammasome-mediated cytokines IL-1β and IL-18. RESULTS: Disulfiram induced a dose-dependent inhibition of ASC speck formation and IL-1β release in cellular assays in vitro. In vivo, treatment with disulfiram, but not with vehicle and less mometasone, inhibited SDS-induced eczema. This was demonstrated by significantly lower erythema and total perfusion values assessed by mexameter and laser speckle imaging for disulfiram compared to vehicle (p < 0.001) and/or mometasone (p < 0.001). Also, corneocyte IL-18 levels were significantly reduced after application of disulfiram compared to vehicle (p < 0.001). CONCLUSION: We show that disulfiram is a dose-dependent inhibitor of inflammasome pathway activation in vitro and inhibitor of SDS-induced eczema in vivo. Topical application of disulfiram represents a potential treatment option for irritant contact dermatitis

A semi-automated intestinal organoid screening method demonstrates epigenetic control of epithelial maturation

The intestinal epithelium maintains an important barrier throughout life. It consists of several epithelial cell lineages that are derived from LGR5+ intestinal stem cells. Although epigenetic regulation of embryonic stem cell differentiation is well established, its role in adult stem cell systems such as the intestinal epithelium is still undefined. Yet, targeting of epigenetic regulatory enzymes may be relevant for new therapeutics, for example in cancer treatment. Here, we combine a newly established organoid toolbox with an epigenetic probe library to identify epigenetic regulators of intestinal epithelial biology. We discover several probes that alter intestinal epithelial biology including those targeting HDACs, EP300/CREBBP, LSD1, and type I PRMTs. We conclude that epigenetic modifiers are primarily involved in mediating maturation of the epithelium rather than dictating specific cell lineage differentiation. Furthermore, we show that inhibiting type I PRMTs, which leads to epithelial maturation, blocks the growth of adenoma but not normal organoid cultures. Thus, epigenetic probes are a powerful tool in defining biological processes and demonstrate therapeutic potential

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

<p>Abstract</p> <p>Background</p> <p>Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts.</p> <p>Results</p> <p>To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (<it>e.g</it>., for biomolecular sequences, alignments, structures) and functionality (<it>e.g</it>., to parse/write standard file formats).</p> <p>Conclusions</p> <p>PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at <url>http://muralab.org/PaPy</url>, and includes extensive documentation and annotated usage examples.</p