Rapid Countermeasure Discovery against Francisella tularensis Based on a Metabolic Network Reconstruction

Abstract

In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of active versus tested compounds over an elapsed time period of 32 weeks, from pathogen strain identification to selection and validation of novel antimicrobial compounds.

In silicoidentification of metabolic enzyme drug targets inBurkholderia pseudomallei

“…Methods for therapeutic target discovery based on metabolic pathway analysis and metabolic network modeling have become very popular in the last ten years. Numerous studies have identified candidate drug targets in various bacterial (27,34,(91)(92)(93)(94)(95)(96)(97)(98)(99)(100)(101)(102), fungal (102) and protosoan (31,(102)(103)(104)(105) pathogens using a variety of methods to analyze metabolic pathways and networks. One method employs chokepoint analysis to identify metabolic enzymes that are critical to the pathogen, because they uniquely consume and/or produce certain metabolites.…”

Structural and functional characterization of M. tuberculosis sedoheptulose- 7-phosphate isomerase, a critical enzyme involved in lipopolysaccharide biosynthetic pathway

“…However, their crystallographic asymmetric unit contains dimer and functional tetramers were obtained using two-fold crystallographic symmetry. The H. pylori GmhA is the only homologue, which was observed as homodimer in solution 15 , 16 .…”

Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens

“…A multidisciplinary approach was applied to F. tularensis to select a group of enzymes as drug targets and ~20,000 small-molecule compounds were screened to list potential inhibitors against these targets (Chaudhury et al, 2013 ). A set of 40 candidate compounds was identified for antimicrobial activity against F. tularensis .…”