slv-319 and Disease-Models--Animal

When Zika virus emerged as a public health emergency there were no drugs or vaccines approved for its prevention or treatment. We used a high-throughput screen for Zika virus protease inhibitors to identify several inhibitors of Zika virus infection. We expressed the NS2B-NS3 Zika virus protease and conducted a biochemical screen for small-molecule inhibitors. A quantitative structure-activity relationship model was employed to virtually screen ∼138,000 compounds, which increased the identification of active compounds, while decreasing screening time and resources. Candidate inhibitors were validated in several viral infection assays. Small molecules with favorable clinical profiles, especially the five-lipoxygenase-activating protein inhibitor, MK-591, inhibited the Zika virus protease and infection in neural stem cells. Members of the tetracycline family of antibiotics were more potent inhibitors of Zika virus infection than the protease, suggesting they may have multiple mechanisms of action. The most potent tetracycline, methacycline, reduced the amount of Zika virus present in the brain and the severity of Zika virus-induced motor deficits in an immunocompetent mouse model. As Food and Drug Administration-approved drugs, the tetracyclines could be quickly translated to the clinic. The compounds identified through our screening paradigm have the potential to be used as prophylactics for patients traveling to endemic regions or for the treatment of the neurological complications of Zika virus infection.

Topics: Animals; Antiviral Agents; Artificial Intelligence; Chlorocebus aethiops; Disease Models, Animal; Drug Evaluation, Preclinical; High-Throughput Screening Assays; Immunocompetence; Inhibitory Concentration 50; Methacycline; Mice, Inbred C57BL; Protease Inhibitors; Quantitative Structure-Activity Relationship; Small Molecule Libraries; Vero Cells; Zika Virus; Zika Virus Infection

The application of the evolutionary fragment-based de novo design tool TOPology Assigning System (TOPAS), starting from a known CB1R (CB-1 receptor) ligand, followed by further refinement principles, including pharmacophore compliance, chemical tractability, and drug likeness, allowed the identification of benzodioxoles as a novel CB1R inverse agonist series. Extensive multidimensional optimization was rewarded by the identification of promising lead compounds, showing in vivo activity. These compounds reversed the CP-55940-induced hypothermia in Naval Medical Research Institute (NMRI) mice and reduced body-weight gain, as well as fat mass, in diet-induced obese Sprague-Dawley rats. Herein, we disclose the tools and strategies that were employed for rapid hit identification, synthesis and generation of structure-activity relationships, ultimately leading to the identification of (+)-[( R)-2-(2,4-dichloride-phenyl)-6-fluoro-2-(4-fluoro-phenyl)-benzo[1,3]dioxol-5-yl]-morpholin-4-yl-methanone ( R)-14g . Biochemical, pharmacokinetic, and pharmacodynamic characteristics of ( R)-14g are discussed.

Topics: Animals; Anti-Obesity Agents; Benzodioxoles; Body Weight; Crystallography, X-Ray; Cyclohexanols; Disease Models, Animal; Dose-Response Relationship, Drug; Drug Design; Humans; Hypothermia; Ligands; Male; Mice; Microsomes; Models, Molecular; Molecular Structure; Obesity; Rats; Rats, Sprague-Dawley; Receptor, Cannabinoid, CB1; Structure-Activity Relationship