Drug Target Selection for Trypanosoma cruzi Metabolism by Metabolic Control Analysis and Kinetic Modeling

Abstract

In the search for therapeutic targets in the intermediary metabolism of trypanosomatids the gene essentiality criterion as determined by using knock-out and knock-down genetic strategies is commonly applied. As most of the evaluated enzymes/transporters have turned out to be essential for parasite survival, additional criteria and approaches are clearly required for suitable drug target prioritization. The fundamentals of Metabolic Control Analysis (MCA; an approach in the study of control and regulation of metabolism) and kinetic modeling of metabolic pathways (a bottom-up systems biology approach) allow quantification of the degree of control that each enzyme exerts on the pathway flux (flux control coefficient) and metabolic intermediate concentrations (concentration control coefficient). MCA studies have demonstrated that metabolic pathways usually have two or three enzymes with the highest control of flux; their inhibition has more negative effects on the pathway function than inhibition of enzymes exerting low flux control. Therefore, the enzymes with the highest pathway control are the most convenient targets for therapeutic intervention. In this review, the fundamentals of MCA as well as experimental strategies to determine the flux control coefficients and metabolic modeling are analyzed. MCA and kinetic modeling have been applied to trypanothione metabolism in Trypanosoma cruzi and the model predictions subsequently validated in vivo. The results showed that three out of ten enzyme reactions analyzed in the T. cruzi anti-oxidant metabolism were the most controlling enzymes. Hence, MCA and metabolic modeling allow a further step in target prioritization for drug development against trypanosomatids and other parasites.

Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approaches

“…The closer the coefficient is to 1, the higher the enzyme impact on the flux. Thus, this coefficient differs from the concept of rate-limiting enzyme, which is commonly defined as the enzyme which catalyzes the slowest step in the pathway and corresponds to a qualitative evaluation of the enzyme impact on the pathway flux [15][16][17] .…”

“…The COPASI models provide satisfactory predicted fluxes, as well as the ANN model, with a marked preference for the grey-box approach. Subsequently, the flux control coefficients of the enzymes ( C J E ) are calculated and allow the identification of the key enzymes involved in flux control [15][16][17] . Taken together, these models enable the construction of the pathway from experimental data and the determination of the main controlling enzymes in the system, revealing the relevance of both the traditional white-box approach and the novel grey-and black-box Figure 1.…”

“…For purposes of analyzing the pathway flux control and identifying the key enzymes involved in the flux control, the flux control coefficient of each enzyme ( C J E ) is calculated with each model (ANNs and metabolic networks). This measure, generally used in Metabolic Control Analysis (MCA), allows us to assess quantitatively the impact of the enzyme on the pathway flux [15][16][17] . Here, C J E is determined in an analytical way using the formula mentioned below (9):…”

Gamma-glutamylcysteine synthetase and tryparedoxin 1 exert high control on the antioxidant system in Trypanosoma cruzi contributing to drug resistance and infectivity

“…Nevertheless, their metabolic validation as potential sites for therapeutic intervention is still a pending experimental issue. In this regard, an approach is to determine the role that each enzyme has in controlling the T(SH) 2 metabolism pathway, because inhibition of the most controlling pathway enzymes would affect more the pathway function than inhibition of enzymes exerting limited control (for a review see [22,23].…”

Chagas Disease Treatment: From New Therapeutic Targets to Drug Discovery and Repositioning

“…Saavedra et al [8] explore new fields in drug target development and open new interrogations about target prioritization. The authors analyse the fundamentals of Metabolic Control Analysis and kinetic modelling of metabolic pathways and apply them to the trypanothion metabolism of T. cruzi.…”