Open Access Highly Accessed Methodology article

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

Susanna Bazzani*, Andreas Hoppe* and Hermann-Georg Holzhütter

Author Affiliations

Institut für Biochemie, Charite-Universitätsmedizin, Reinickendorfer Str. 61, Haus 10, 13347 Berlin

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BMC Systems Biology 2012, 6:118  doi:10.1186/1752-0509-6-118

Published: 31 August 2012



The 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.


Using 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.


Genome-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.

Plasmodium falciparum; Human hepatocyte; Drug targets; Drug selectivity; Genome-scale networks; Reduced fitness; Flux balance analysis