Validated antimalarial drug target discovery using genome-scale metabolic modeling

Given the rapid resistance of <i>Plasmodium falciparum</i> to antimalarial drugs, there is a continual need for new treatments. A genome-scale metabolic (GSM) model was developed with integrated metabolomics and constraint-based, experimental flux-balance data to predict genes essential for <i>P. falciparum</i> growth as drug targets. We selected the highly ranked <i>P. falciparum</i> UMP-CMP kinase (UCK) to test its necessity and the ability to inhibit parasite growth in the presence of inhibitors. Conditional deletion mutants using the DiCre recombinase system, generated by CRISPR-Cas genome editing, exhibited defective asexual growth and stage-specific developmental arrest. Based on <i>in silico</i> and <i>in vitro</i> screening, inhibitors were identified that are selective for <i>P. falciparum</i> UCK and exhibit antiparasitic activity. This study, for the first time, shows assertions from a GSM model identifying novel, validated "druggable" targets. These findings show a role for GSM models in antimalarial drug discovery and identify <i>P. falciparum</i> UCK as a novel, valid malaria drug target.