BILN: A Human-Readable Line Notation for Complex Peptides.

We present an easy, human-readable line notation to describe even complex peptides.

Nanchangmycin regulates FYN, PTK2, and MAPK1/3 to control the fibrotic activity of human hepatic stellate cells.

Chronic liver injury causes fibrosis, characterized by the formation of scar tissue resulting from excessive accumulation of extracellular matrix (ECM) proteins. Hepatic stellate cell (HSC) myofibroblasts are the primary cell type responsible for liver fibrosis, yet there are currently no therapies directed at inhibiting the activity of HSC myofibroblasts. To search for potential anti-fibrotic compounds, we performed a high-throughput compound screen in primary human HSC myofibroblasts and identified 19 small molecules that induce HSC inactivation, including the polyether ionophore nanchangmycin (NCMC). NCMC induces lipid re-accumulation while reducing collagen expression, deposition of collagen in the extracellular matrix, cell proliferation, and migration. We find that NCMC increases cytosolic Ca2+ and reduces the phosphorylated protein levels of FYN, PTK2 (FAK), MAPK1/3 (ERK2/1), HSPB1 (HSP27), and STAT5B. Further, depletion of each of these kinases suppress COL1A1 expression. These studies reveal a signaling network triggered by NCMC to inactivate HSC myofibroblasts and reduce expression of proteins that compose the fibrotic scar. Identification of the antifibrotic effects of NCMC and the elucidation of pathways by which NCMC inhibits fibrosis provide new tools and therapeutic targets that could potentially be utilized to combat the development and progression of liver fibrosis.

Screening for Inhibitors of YAP Nuclear Localization Identifies Aurora Kinase A as a Modulator of Lung Fibrosis.

Idiopathic pulmonary fibrosis is a progressive lung disease with limited therapeutic options that is characterized by pathological fibroblast activation and aberrant lung remodeling with scar formation. YAP (Yes-associated protein) is a transcriptional coactivator that mediates mechanical and biochemical signals controlling fibroblast activation. We previously identified HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase inhibitors (statins) as YAP inhibitors based on a high-throughput small-molecule screen in primary human lung fibroblasts. Here we report that several Aurora kinase inhibitors were also identified from the top hits of this screen. MK-5108, a highly selective inhibitor for AURKA (Aurora kinase A), induced YAP phosphorylation and cytoplasmic retention and significantly reduced profibrotic gene expression in human lung fibroblasts. The inhibitory effect on YAP nuclear translocation and profibrotic gene expression is specific to inhibition of AURKA, but not Aurora kinase B or C, and is independent of the Hippo pathway kinases LATS1 and LATS2 (Large Tumor Suppressor 1 and 2). Further characterization of the effects of MK-5108 demonstrate that it inhibits YAP nuclear localization indirectly via effects on actin polymerization and TGFß (Transforming Growth Factor ß) signaling. In addition, MK-5108 treatment reduced lung collagen deposition in the bleomycin mouse model of pulmonary fibrosis. Our results reveal a novel role for AURKA in YAP-mediated profibrotic activity in fibroblasts and highlight the potential of small-molecule screens for YAP inhibitors for identification of novel agents with antifibrotic activity.

Screening for YAP Inhibitors Identifies Statins as Modulators of Fibrosis.

Idiopathic pulmonary fibrosis is a lung disease with limited therapeutic options that is characterized by pathological fibroblast activation and aberrant lung remodeling with scar formation. YAP (Yes-associated protein) is a transcriptional coactivator that mediates mechanical and biochemical signals controlling fibroblast activation. In this study, we developed a high-throughput small-molecule screen for YAP inhibitors in primary human lung fibroblasts. Multiple HMG-CoA (hydroxymethylglutaryl-coenzyme A) reductase inhibitors (statins) were found to inhibit YAP nuclear localization via induction of YAP phosphorylation, cytoplasmic retention, and degradation. We further show that the mevalonate pathway regulates YAP activation, and that simvastatin treatment reduces fibrosis markers in activated human lung fibroblasts and in the bleomycin mouse model of pulmonary fibrosis. Finally, we show that simvastatin modulates YAP in vivo in mouse lung fibroblasts. Our results highlight the potential of small-molecule screens for YAP inhibitors and provide a mechanism for the antifibrotic activity of statins in idiopathic pulmonary fibrosis.

Designing Multi-target Compound Libraries with Gaussian Process Models.

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design.

Assay Related Target Similarity (ARTS) - chemogenomics approach for quantitative comparison of biological targets.

Computer-based chemogenomics approaches compare macromolecular drug targets based on their amino acid sequences or derived properties, by similarity of their ligands, or according to ligand-target interaction models. Here we present ARTS (Assay Related Target Similarity) as a quantitative index that estimates target similarity directly from measured affinities of a set of probe compounds. This approach reduces the risk of deducing artificial target relationships from mutually inactive compounds. ARTS implements a scoring scheme that matches intertarget similarity based on dose-response measurements. While all experimentally derived target similarities have a tendency to be data set-dependent, we demonstrate that ARTS depends less on the used data set than the commonly used Pearson correlation or Tanimoto index.

High-content analysis of CCR2 antagonists on human primary monocytes.

The monocyte chemoattractant protein 1 (MCP-1)-driven activation of CC-type chemokine receptor 2 (CCR2) is one of the early key events to induce monocyte migration toward centers of inflammation. In this work, the authors analyzed MCP-1 internalization into primary human monocytes using partially automated liquid handling, automated fluorescence microscopic imaging, and a specific image analysis algorithm. A fluorophore-conjugated form of MCP-1 was rapidly endocytosed and retained by the monocytes. The CCR2 dependency of the MCP-1 internalization was demonstrated by the use of BMS CCR2 22, a CCR2-specific antagonist. The apparent inhibitory potencies of a series of small-molecule CCR2 antagonists were determined and compared in five assay formats, including the high-content analysis assay described in this work. Interestingly, some but not all antagonists showed markedly different inhibitory behaviors in the five readout systems, with an up to more than 100-fold difference between the highest and the lowest apparent inhibitory potencies. These findings raise the distinct possibility that some CCR2 antagonists are capable of discriminating between different functional states of the CCR2 receptor(s) and suggest strategies for the identification of functionally selective CCR2 antagonists with increased therapeutic advantage over nonselective antagonists.

G-protein-coupled receptor-focused drug discovery using a target class platform approach.

In recent years, several large pharmaceutical companies have taken a novel approach to drug discovery biology and chemistry in that they channel their efforts with respect to particular target classes, such as G-protein-coupled receptors (GPCRs), toward dedicated, specialized teams. Benefits of such an organizational structure are the prospects of establishing several target-family-specific experimental techniques and skill sets, thereby enabling a comprehensive functional profiling of drug candidates in different pharmacological respects. In this context, the recently increased number of reports on GPCR ligand-biased signaling has further spurred the efforts in the pharmaceutical industry toward broader biological characterization of the test compounds, for example employing high-content screening to analyze different GPCR ligand-induced signaling pathways. The knowledge of the disease-relevant functional properties of the small molecule GPCR ligands enables target-specific chemical optimization and GPCR-subclass-directed library design. In the case of GPCRs, where little--although at present slowly expanding--structural information on the targets is available, the modeling of GPCR structures crucially depends on biological validation (typically supported by site-directed mutagenesis of the GPCR ligand binding site). In this review, we aim to recapitulate efforts in the pharmaceutical industry to address GPCR-directed drug discovery in a target-class-directed platform approach: establishing GPCR-specific biological assay panels and creating computational chemistry methods for finding and optimizing small molecules modulating the activity of GPCRs.