Validated Antimalarial Drug Target Discovery using Genome-Scale Metabolic Modelling

Abstract

Given the rapid resistance of Plasmodium falciparum to antimalarial drugs, there is a continual need for new treatments. A genome-scale metabolic (GSM) model was developed with integrated omic and constraint-based, experimental flux-balance data to predict genes essential for P. falciparum growth as drug targets. We selected the highly ranked P. falciparum UMP-CMP kinase (UCK) to test its necessity and the ability to inhibit growth with 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 in silico and in vitro screening, inhibitors were identified that are selective for P. falciparum 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 P. falciparum UCK as a novel, valid malaria drug target.