Tissue dyslipidemia in salmonella-infected rats treatTissue dyslipidemia in salmonella-infected rats treated with amoxillin and pefloxac

Background: This study investigated the effects of salmonella infection and its chemotherapy on lipid metabolism in tissues of rats infected orally with Salmonella typhimurium and treated intraperitoneally with pefloxacin and amoxillin. Methods: Animals were infected with Salmonella enterica serovar Typhimurium strain TA 98. After salmonellosis was confirmed, they were divided into 7 groups of 5 animals each. While one group served as infected control group, three groups were treated with amoxillin (7.14 mg/kg body weight, 8 hourly) and the remaining three groups with pefloxacin (5.71mg/kg body weight, 12 hourly) for 5 and 10 days respectively. Uninfected control animals received 0.1ml of vehicle. Rats were sacrificed 24h after 5 and 10 days of antibiotic treatment and 5 days after discontinuation of antibiotic treatment. Their corresponding controls were also sacrificed at the same time point. Blood and tissue lipids were then evaluated. Results: Salmonella infection resulted in dyslipidemia characterised by increased concentrations of free fatty acids (FFA) in plasma and erythrocyte, as well as enhanced cholesterogenesis, hypertriglyceridemia and phospholipidosis in plasma, low density lipoprotein-very low density lipoprotein (LDL-VLDL), erythrocytes, erythrocyte ghost and the organs. The antibiotics reversed the dyslipidemia but not totally. A significant correlation was observed between fecal bacterial load and plasma cholesterol (r=0.456, p<0.01), plasma triacyglycerols (r=0.485, p<0.01), plasma phospholipid (r=0.414, p<0.05), plasma free fatty acids (r=0.485, p<0.01), liver phospholipid (r=0.459, p<0.01) and brain phospholipid (r=0.343, p<0.05). Conclusion: The findings of this study suggest that salmonella infection in rats and its therapy with pefloxacin and amoxillin perturb lipid metabolism and this perturbation is characterised by cholesterogenesis

Molecular docking for predictive toxicology

Molecular docking is an in silico method widely applied in drug discovery programs to predict the binding mode of a given molecule interacting with a specific biological target. This computational technique is today emerging also in the field of predictive toxicology for regulatory purposes, being for instance successfully applied to develop classification models for the prediction of the endocrine disruptor potential of chemicals. Herein, we describe the protocol for adapting molecular docking to the purposes of predictive toxicology