isoxicam 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 study aimed to predict effective human jejunal permeability (P(eff)) using a biophysical model based on parametrized paracellular, aqueous boundary layer, and transcellular permeabilities, and the villus-fold surface area expansion factor (k(VF)). Published human jejunal data (119 P(eff), 53 compounds) were analyzed by a regression procedure incorporating a dual-pore size paracellular model. Transcellular permeability, scaled by k(VF), was equated to that of Caco-2 at pH 6.5. The biophysical model predicted human jejunal permeability data within the experimental uncertainty. This investigation revealed several surprising predictions: (i) many molecules permeate predominantly (but not exclusively) by the paracellular route, (ii) the aqueous boundary layer thickness in the intestinal perfusion experiments is larger than expected, (iii) the mucosal surface area in awake humans is apparently nearly entirely accessible to drug absorption, and (iv) the relative "leakiness" of the human jejunum is not so different from that observed in a number of published Caco-2 studies.

Topics: Animals; Disease Models, Animal; Dogs; Humans; Jejunal Diseases; Kidney Diseases; Models, Biological; Permeability; Porosity; Regression Analysis