75 research outputs found

    G Protein-Coupled Receptor Kinase 6 (GRK6) Regulates Insulin Processing and Secretion via Effects on Proinsulin Conversion to Insulin

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    Recent studies identified a missense mutation in the gene coding for G protein-coupled receptor kinase 6 (GRK6) that segregates with type 2 diabetes (T2D). To better understand how GRK6 might be involved in T2D, we used pharmacological inhibition and genetic knockdown in the mouse β-cell line, MIN6, to determine whether GRK6 regulates insulin dynamics. We show inhibition of GRK5 and GRK6 increased insulin secretion but reduced insulin processing while GRK6 knockdown revealed these same processing defects with reduced levels of cellular insulin. GRK6 knockdown cells also had attenuated insulin secretion but enhanced proinsulin secretion consistent with decreased processing. In support of these findings, we demonstrate GRK6 rescue experiments in knockdown cells restored insulin secretion after glucose treatment. The altered insulin profile appears to be caused by changes in the proprotein convertases, the enzymes responsible for proinsulin to insulin conversion, as GRK6 knockdown resulted in significantly reduced convertase expression and activity. To identify how the GRK6-P384S mutation found in T2D patients might affect insulin processing, we performed biochemical and cell biological assays to study the properties of the mutant. We found that while GRK6-P384S was more active than WT GRK6, it displayed a cytosolic distribution in cells compared to the normal plasma membrane localization of GRK6. Additionally, GRK6 overexpression in MIN6 cells enhanced proinsulin processing, while GRK6-P384S expression had little effect. Taken together, our data show that GRK6 regulates insulin processing and secretion in a glucose-dependent manner and provide a foundation for understanding the contribution of GRK6 to T2D

    CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding

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    One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small-molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small-molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared and openly published. CACHE will launch three new benchmarking exercises every year. The outcomes will be better prediction methods, new small-molecule binders for target proteins of importance for fundamental biology or drug discovery and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins. [Figure not available: see fulltext.

    Small molecule epigenetic screen identifies novel EZH2 and HDAC inhibitors that target glioblastoma brain tumor-initiating cells

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    Glioblastoma (GBM) is the most lethal and aggressive adult brain tumor, requiring the development of efficacious therapeutics. Towards this goal, we screened five genetically distinct patient-derived brain-tumor initiating cell lines (BTIC) with a unique collection of small molecule epigenetic modulators from the Structural Genomics Consortium (SGC). We identified multiple hits that inhibited the growth of BTICs in vitro, and further evaluated the therapeutic potential of EZH2 and HDAC inhibitors due to the high relevance of these targets for GBM. We found that the novel SAM-competitive EZH2 inhibitor UNC1999 exhibited low micromolar cytotoxicity in vitro on a diverse collection of BTIC lines, synergized with dexamethasone (DEX) and suppressed tumor growth in vivo in combination with DEX. In addition, a unique brain-penetrant class I HDAC inhibitor exhibited cytotoxicity in vitro on a panel of BTIC lines and extended survival in combination with TMZ in an orthotopic BTIC model in vivo. Finally, a combination of EZH2 and HDAC inhibitors demonstrated synergy in vitro by augmenting apoptosis and increasing DNA damage. Our findings identify key epigenetic modulators in GBM that regulate BTIC growth and survival and highlight promising combination therapies

    C9ORF72 interaction with cofilin modulates actin dynamics in motor neurons.

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    Intronic hexanucleotide expansions in C9ORF72 are common in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, but it is unknown whether loss of function, toxicity by the expanded RNA or dipeptides from non-ATG-initiated translation are responsible for the pathophysiology. We determined the interactome of C9ORF72 in motor neurons and found that C9ORF72 was present in a complex with cofilin and other actin binding proteins. Phosphorylation of cofilin was enhanced in C9ORF72-depleted motor neurons, in patient-derived lymphoblastoid cells, induced pluripotent stem cell-derived motor neurons and post-mortem brain samples from ALS patients. C9ORF72 modulates the activity of the small GTPases Arf6 and Rac1, resulting in enhanced activity of LIM-kinases 1 and 2 (LIMK1/2). This results in reduced axonal actin dynamics in C9ORF72-depleted motor neurons. Dominant negative Arf6 rescues this defect, suggesting that C9ORF72 acts as a modulator of small GTPases in a pathway that regulates axonal actin dynamics

    A Comparison Of Broad Versus Deep Auditory Menu Structures

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    Objective: The primary purpose of this experiment was to gain a greater understanding of the utilization of working memory when interacting with a speech-enabled interactive voice response (IVR) system. Background: A widely promoted guideline advises limiting IVR menus to five or fewer items because of constraints of the human memory system, commonly citing Miller\u27s (1956) paper. The authors argue that Miller\u27s paper does not, in fact, support this guideline. Furthermore, applying modern theories of working memory leads to the opposite conclusion - that reducing menu length by creating a deeper structure is actually more demanding of users\u27 working memories and leads to poorer performance and satisfaction. Method: Participants took a working memory capacity test and then attempted to complete a series of e-mail tasks using one of two IVR designs (functionally equivalent, but one with a broad menu structure and the other with a deep structure). Results: Users of the broad-structure IVR performed better and were more satisfied than users of the deep-structure IVR. Furthermore, this effect was more pronounced for those with low working memory capacity. Conclusion: Results indicate that creating a deeper structure is more demanding of working memory resource than the alternative of longer, shallower menus. Application: This experiment has important practical implications for all systems with auditory menus (particularly IVRs) because it provides empirical evidence refuting a widely promoted design practice. Copyright © 2008, Human Factors and Ergonomics Society

    IMDA/Retro-Mannich Approach to cis

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