Enhanced In Vivo Activity of Cefditoren in Pre-Immunized Mice against Penicillin-Resistant S. pneumoniae (Serotypes 6B, 19F and 23F) in a Sepsis Model

Background Specific antibodies are likely to be present before S. pneumoniae infection. We explored cefditoren (CDN) total and free values of serum concentrations exceeding the MIC (t>MIC) related to efficacy in a mice sepsis model, and the effect of specific gammaglobulins on in-vitro phagocytosis and in-vivo efficacy. Methodology/Principal Findings We used three pneumococcal isolates (serotype, MIC of CDN): Strain 1 (6B, 1 µg/ml), Strain 2 (19F, 2 µg/ml) and Strain 3 (23F, 4 µg/ml). Hyperimmune serum (HS) was obtained from mice immunized with heat-inactivated strains. In-vitro, phagocytosis by HS diluted 1/10 in presence/absence of sub-inhibitory concentrations was measured by flow cytometry including fluorescent bacteria and a neutrophil cell line. In-vivo dose-ranging experiments with HS (dilutions 1/2–1/16) and CDN (6.25 mg/kg–100 mg/kg tid for 48 h) were performed to determine the minimal protective dilution/dose (highest survival) and the non-protective highest dilution/dose (highest mortality: HS-np dilution and CDN-np dose) over 7 days. Efficacy of CDN-np in animals pre-immunized with HS-np (combined strategy) was explored and blood bacterial clearance determined. The CDN measured protein binding was 86.9%. In-vitro, CDN significantly increased phagocytosis (vs. HS 1/10). In non pre-immunized animals, t>MIC values for CDN of ≈35% (total) and ≈19% (free) were associated with 100% survival. Significant differences in survival were found between HS-np alone (≤20%) or CDN-np alone (≤20%) vs. the combined strategy (90%, 60% and 60% for Stains 1, 2 and 3), with t>MIC (total/free) of 22.8%/14.3%, 26.8%/16.0%, and 22.4%/12.7% for Strains 1, 2 and 3, respectively. Prior to the second dose (8 h), median bacterial counts were significantly lower in animals surviving vs. dead at day 7. Conclusions/Significance In mice (CDN protein binding similar to humans) total t>MIC values of ≈35% (≈19% free) were efficacious, with a decrease in the required values in pre-immunized animals. This reinforces that immunoprotection to overcome resistance may provide lifesaving strategies.This study was supported by an unrestricted grant from Tedec-Meiji Farma S.A., Madrid, Spain. Tedec-Meiji Farma S.A. had a role in providing reagents, materials and analysis toolsPeer reviewe

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism

Exploring new physics frontiers through numerical relativity

The demand to obtain answers to highly complex problems within strong-field gravity has been met with significant progress in the numerical solution of Einstein's equations - along with some spectacular results - in various setups. We review techniques for solving Einstein's equations in generic spacetimes, focusing on fully nonlinear evolutions but also on how to benchmark those results with perturbative approaches. The results address problems in high-energy physics, holography, mathematical physics, fundamental physics, astrophysics and cosmology