The in vitro screening core, overseen by Drs Nancy Connell and Barry Kreiswirth, will provide comprehensive screening services for susceptibility and cytotoxicity determination for candidate compounds provided by the project directors. The standard wild type bacterial strains represent Mycobacterium tuberculosis (both actively growing and non-replicative), other pathogenic mycobacterial species, the ESKAPE pathogens (Enterococcus faecium. Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) and bacterial Select Agents (Bacillus anthracis, Francisella tularensis. Yersinia pestis, Burkholderia mallei, Burkholderia pseudomallei, Rickettsia prowazekii, and Coxiella burnetii). In addition, the Public Health Research Institute has extensive collections of bacterial and fungal pathogens in collaboration with private, public and VA hospitals in the New York/New Jersey Metropolitan area, as well as hospitals throughout the world. The bacterial strain collection of drug susceptible and drug resistant organisms is derived largely from bloodstream, soft-tissue, burn, wound, pustules, and respiratory fluids specimens. Finally, the in vitro screening core will provide cytotoxicity screening in mammalian cells (VERO, J774.1, RAW, THP1) and intracellular antibiotic efficacy studies.
|Chu, John; Vila-Farres, Xavier; Inoyama, Daigo et al. (2016) Discovery of MRSA active antibiotics using primary sequence from the human microbiome. Nat Chem Biol 12:1004-1006|
|Perryman, Alexander L; Stratton, Thomas P; Ekins, Sean et al. (2016) Predicting Mouse Liver Microsomal Stability with ""Pruned"" Machine Learning Models and Public Data. Pharm Res 33:433-49|
|Ekins, Sean; Perryman, Alexander L; Clark, Alex M et al. (2016) Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015). J Chem Inf Model 56:1332-43|
|Ekins, Sean; Madrid, Peter B; Sarker, Malabika et al. (2015) Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery. PLoS One 10:e0141076|