Selective estrogen receptor modulators against Gram-positive and Gram-negative bacteria: an experimental study

Drug metabolism of ciprofloxacin, ivacaftor, and raloxifene by Pseudomonas aeruginosa cytochrome P450 CYP107S1

Drug metabolism is one of the main processes governing the pharmacokinetics and toxicity of drugs via their chemical biotransformation and elimination. In humans, the liver, enriched with cytochrome P450 (CYP) enzymes, plays a major metabolic and detoxification role. The gut microbiome and its complex community of microorganisms can also contribute to some extent to drug metabolism. However, during an infection when pathogenic microorganisms invade the host, our knowledge of the impact on drug metabolism by this pathobiome remains limited. The intrinsic resistance mechanisms and rapid metabolic adaptation to new environments often allow the human bacterial pathogens to persist, despite the many antibiotic therapies available. Here, we demonstrate that a bacterial CYP enzyme, CYP107S1, from Pseudomonas aeruginosa, a predominant bacterial pathogen in cystic fibrosis patients, can metabolize multiple drugs from different classes. CYP107S1 demonstrated high substrate promiscuity and allosteric properties much like human hepatic CYP3A4. Our findings demonstrated binding and metabolism by the recombinant CYP107S1 of fluoroquinolone antibiotics (ciprofloxacin and fleroxacin), a cystic fibrosis transmembrane conductance regulator potentiator (ivacaftor), and a selective estrogen receptor modulator antimicrobial adjuvant (raloxifene). Our in vitro metabolism data were further corroborated by molecular docking of each drug to the heme active site using a CYP107S1 homology model. Our findings raise the potential for microbial pathogens modulating drug concentrations locally at the site of infection, if not systemically, via CYP-mediated biotransformation reactions. To our knowledge, this is the first report of a CYP enzyme from a known bacterial pathogen that is capable of metabolizing clinically utilized drugs.

Prediction of Drug-Drug-Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling

Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug-gene interactions (DGIs), drug-drug interactions (DDIs) and drug-drug-gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted C_max and 80% of AUC_last values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies.

Gram-Selective Antibacterial Activity of Mixed-Charge 2D-MoS2

Development of nanomaterial-based antibiotics can be the most potent alternative due to the increasing resistance against conventional antibiotics. But one of the important parameters in development of antibacterial agent is...