21 research outputs found

    2-Mercapto-Quinazolinones as Inhibitors of Type II NADH Dehydrogenase and Mycobacterium tuberculosis:Structure-Activity Relationships, Mechanism of Action and Absorption, Distribution, Metabolism, and Excretion Characterization

    Get PDF
    <i>Mycobacterium tuberculosis</i> (<i>MTb</i>) possesses two nonproton pumping type II NADH dehydrogenase (NDH-2) enzymes which are predicted to be jointly essential for respiratory metabolism. Furthermore, the structure of a closely related bacterial NDH-2 has been reported recently, allowing for the structure-based design of small-molecule inhibitors. Herein, we disclose <i>MTb</i> whole-cell structure–activity relationships (SARs) for a series of 2-mercapto-quinazolinones which target the <i>ndh</i> encoded NDH-2 with nanomolar potencies. The compounds were inactivated by glutathione-dependent adduct formation as well as quinazolinone oxidation in microsomes. Pharmacokinetic studies demonstrated modest bioavailability and compound exposures. Resistance to the compounds in <i>MTb</i> was conferred by promoter mutations in the alternative nonessential NDH-2 encoded by <i>ndhA</i> in <i>MTb</i>. Bioenergetic analyses revealed a decrease in oxygen consumption rates in response to inhibitor in cells in which membrane potential was uncoupled from ATP production, while inverted membrane vesicles showed mercapto-quinazolinone-dependent inhibition of ATP production when NADH was the electron donor to the respiratory chain. Enzyme kinetic studies further demonstrated noncompetitive inhibition, suggesting binding of this scaffold to an allosteric site. In summary, while the initial <i>MTb</i> SAR showed limited improvement in potency, these results, combined with structural information on the bacterial protein, will aid in the future discovery of new and improved NDH-2 inhibitors

    A Design Approach for Collaboration Processes: A Multi-Method Design Science Study in Collaboration Engineering

    Get PDF
    Collaboration Engineering is an approach for the design and deployment of repeatable collaboration processes that can be executed by practitioners without the support of collaboration professionals such as facilitators. A critical challenge in Collaboration Engineering concerns how the design activities have to be executed and which design choices have to be made to create a process design. We report on a four year design science study, in which we developed a design approach for Collaboration Engineering thatincorporates existing process design methods, pattern based design principles, and insights from expert facilitators regarding design challenges and choices. The resulting approach was evaluated and continuously improved in four trials with 37 students. Our findings suggest that this approach is useful to support the design of repeatable collaboration processes. Our study further serves as an example of how a design approach can be developed and improved following a multi-method design science approach.Multi Actor SystemsTechnology, Policy and Managemen

    IC<sub>50</sub> Determination of a test set of compounds.

    No full text
    <p><sup><b>a</b></sup> Coefficient of variation for all IC<sub>50</sub>’s were lower than 1%</p><p>IC<sub>50</sub> Determination of a test set of compounds.</p

    Results of clinical collection compound primary screen.

    No full text
    <p>Panel A. Scatterplot representing the results for the screen at 5 μM. Green circles represent the hits, blue circles are all the other compounds. Panel B. Scatterplot representing the results for the screen at 15 μM. Green circles represent the hits from the 5 μM screen, blue circles are all the other compounds. Panel C. Scatterplot comparing <i>T</i>. <i>cruzi</i> percent inhibition between 5 μM and 15 μM screens. Panel D. Replicates plot for a subset of compounds screened twice at 5 μM (n = 579, R<sup>2</sup> = 0.86).</p

    Analysis of the hits.

    No full text
    <p>Panel A. All the hits from the 5 μM screen were annotated with a general pharmaceutical class. The chart shows the frequency for each class. Panel B. The potencies for all the hits were determined and represented as a frequency table. Bars in red represent CYP51 inhibitors, green = all other classes).</p

    <i>T</i>. <i>cruzi</i> rate-of-kill assay.

    No full text
    <p>Panel A. Outline of the rate-of-kill assay. Numbers are time in hours. Times above the timeline are from addition of the trypomastigotes, times below the line are starting from addition of the infected cells to the plates containing compounds. Panel B. Representative images from untreated wells in the static-cidal assay at the different time-points. Panel C. Rate-of-kill profiles. Left panel shows percent infected cells against time, right panel shows Vero counts against time (n = 3, error bars = standard deviation) for Nifurtimox (top), Benznidazole (middle) and Posaconazole (bottom). Concentrations are as follows (μM) (all compounds were tested at the same concentrations except for Posaconazole, its concentrations are shown between brackets): black circle 50 (1), red triangle 17 (0.3), green square 5.6 (0.1), yellow diamond 1.9 (0.04), blue triangle 0.6 (0.01), pink hexagon 0.2 (0.004), cyan circle 0.07 (0.001), triangle dark yellow 0.</p

    <i>T</i>. <i>cruzi</i> primary screening assay.

    No full text
    <p>Panel A. Schematic outline of the primary screening assay. Numbers are time in hours. Panel B. Image acquisition and analysis. Left-hand side shows an image as obtained from the high-content microscope. The large structures are the nuclei of the host cells and the small punctate structures are the nuclei of the amastigotes. The right-hand panel shows the segmentation carried out by the image analysis algorithm. The nuclei are delineated in red, the Vero cell cytoplasm in white and the amastigotes in yellow.</p

    Replication of host cells and amastigotes.

    No full text
    <p>Panel A. A time-course was carried under assay conditions and plates were fixed every day followed by imaging and analysis. The full circles show the host cell counts and the open circles show the amastigote counts (n = 384 wells, error bars are standard deviations). The doubling time for the amastigotes was determined in the exponential growth window (between 24 and 96 h). Panel B. A time-course was carried out using gamma-irradiated Vero cells. Plates were fixed every day followed by imaging and analysis. The full circles show the host cell counts and the open circles show the amastigote counts (n = 18 wells from a single experiment, error bars are standard deviations).</p
    corecore