Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease

Abstract

BackgroundSystems biology holds promise as a new approach to drug target identification and drug discovery against neglected tropical diseases. Genome-scale metabolic reconstructions, assembled from annotated genomes and a vast array of bioinformatics/biochemical resources, provide a framework for the interrogation of human pathogens and serve as a platform for generation of future experimental hypotheses. In this article, with the application of selection criteria for both Leishmania major targets (e.g. in silico gene lethality) and drugs (e.g. toxicity), a method (MetDP) to rationally focus on a subset of low-toxic Food and Drug Administration (FDA)-approved drugs is introduced.ResultsThis metabolic network-driven approach identified 15 L. major genes as high-priority targets, 8 high-priority synthetic lethal targets, and 254 FDA-approved drugs. Results were compared to previous literature findings and existing high-throughput screens. Halofantrine, an antimalarial agent that was prioritized using MetDP, showed noticeable antileishmanial activity when experimentally evaluated in vitro against L. major promastigotes. Furthermore, synthetic lethality predictions also aided in the prediction of superadditive drug combinations. For proof-of-concept, double-drug combinations were evaluated in vitro against L. major and four combinations involving the drug disulfiram that showed superadditivity are presented.ConclusionsA direct metabolic network-driven method that incorporates single gene essentiality and synthetic lethality predictions is proposed that generates a set of high-priority L. major targets, which are in turn associated with a select number of FDA-approved drugs that are candidate antileishmanials. Additionally, selection of high-priority double-drug combinations might provide for an attractive and alternative avenue for drug discovery against leishmaniasis.

Antileishmanial Activity of Disulfiram and Thiuram Disulfide Analogs in anEx VivoModel System Is Selectively Enhanced by the Addition of Divalent Metal Ions

“…Multiple in vitro studies suggested that disulfiram has a broad antipathogen potential. Upon screening of diverse chemical libraries, we and others reported the activity of disulfiram against intracellular amastigotes of L. donovani (17) and both parasite stages of L. major (18)(19)(20). Disulfiram also showed activity against Mycobacterium tuberculosis, Plasmodium falciparum, and Giardia lamblia (11)(12)(13).…”

“…It also has cytotoxic activity against some cancer cells (14-16). We and others have reported that disulfiram is active at nanomolar concentrations against intracellular amastigotes of L. donovani (17) and against L. major amastigotes (18) or promastigotes (19,20). Studies in BALB/c mice infected with L. major showed that administration of disulfiram at 160 mg/kg of resulted in significant reduction (50%) of the footpad lesion in comparison to sham-treated mice (19).…”

“…Studies in BALB/c mice infected with L. major showed that administration of disulfiram at 160 mg/kg of resulted in significant reduction (50%) of the footpad lesion in comparison to sham-treated mice (19). The in silico evaluation of L. major metabolic networks predicted that the antileishmanial activity of disulfiram may reside in its ability to disturb the transmembrane proton transport system encoded by the LmjF25.1170 and LmjF25.1180 genes (20). The proteins coded by these genes are part of the F-type ATPase ␤ chain complex, which participates in the synthesis of parasite ATP, specifically transporting protons (H ϩ ) across the membrane to generate an electrochemical gradient that powers ATP synthesis (21).…”

Multiscale Model of Mycobacterium tuberculosis Infection Maps Metabolite and Gene Perturbations to Granuloma Sterilization Predictions

“…Computational methods have been successfully applied in the drug discovery pipeline against a number of pathogens (108)(109)(110). Genes (and combinations of genes) that we identify to be important for in vivo survival can now be tested as potential new drug targets using existing drugs or KO strains in animal models.…”

A combined systems and structural modeling approach repositions antibiotics for Mycoplasma genitalium

“…Chavali et al (2012) have extensively reviewed the existing systems modeling approaches to drug discovery. Previously, Raman et al (2008) combined qualitative metabolic modeling with structural modeling to identify potential new druggable Mycobacterium tuberculosis targets.…”