Network-based assessment of the selectivity of metabolic drug targets in Plasmodium falciparum with respect to human liver metabolism

Abstract

BackgroundThe search for new drug targets for antibiotics against Plasmodium falciparum, a major cause of human deaths, is a pressing scientific issue, as multiple resistance strains spread rapidly. Metabolic network-based analyses may help to identify those parasite’s essential enzymes whose homologous counterparts in the human host cells are either absent, non-essential or relatively less essential.ResultsUsing the well-curated metabolic networks PlasmoNet of the parasite Plasmodium falciparum and HepatoNet1 of the human hepatocyte, the selectivity of 48 experimental antimalarial drug targets was analyzed. Applying in silico gene deletions, 24 of these drug targets were found to be perfectly selective, in that they were essential for the parasite but non-essential for the human cell. The selectivity of a subset of enzymes, that were essential in both models, was evaluated with the reduced fitness concept. It was, then, possible to quantify the reduction in functional fitness of the two networks under the progressive inhibition of the same enzymatic activity. Overall, this in silico analysis provided a selectivity ranking that was in line with numerous in vivo and in vitro observations.ConclusionsGenome-scale models can be useful to depict and quantify the effects of enzymatic inhibitions on the impaired production of biomass components. From the perspective of a host-pathogen metabolic interaction, an estimation of the drug targets-induced consequences can be beneficial for the development of a selective anti-parasitic drug.

Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks

“…falciparum metabolism. For example, based on recent findings [25], the pyruvate dehydrogenase activity of the mitochondrial BCKDH complex was included in iPfa, whereas it was absent in the previous GEMs of the malaria parasite, iTH366 [5], PlasmoNet [6] and their modifications [7, 8] (see S1 Methods for more details). The coverage of metabolic enzymes (Fig 1A) is consistent with the ones reported in iTH366 and in the model of the related apicomplexan parasite Toxoplasma gondii , ToxoNet1 [3].…”

“…falciparum , iTH366 [5] and PlasmoNet [6]. Since 2010, these GEMs have been slightly modified to study the metabolism of the parasite in the liver stage [7] or in the blood stages [8]. However, no study, to our knowledge, has developed an independent reconstruction of P .…”

Drug target identification through systems biology

“…e20 are selective to the network of the disease cell (e.g. malaria vs. liver cells [48], malaria vs. erythrocytes [49] and T. brucei vs. erythrocytes) (JR Haanstra et al, unpublished). These studies do not yet deal, however, with the many different host cells in which side effects may occur (e.g.…”

Functional genomics of Plasmodium falciparum using metabolic modelling and analysis

“…The first two models [11, 14] were built using graph-based approach and the following are constraint-based models [10, 12, 13]. …”

“…Holzhutter and co-workers have developed the most recent CBM of the P. falciparum metabolic network [10] by updating their previous PlasmoNet1 model [12]. In PlasmoNet2 [10] they have added new transport reactions based on metabolomics data [30] and removed one reaction according to an updated version of KEGG database.…”