Abstract
To validate therapeutic targets in metabolic pathways of trypanosomatids, the criterion of enzyme essentiality determined by gene knockout or knockdown is usually being applied. Since, it is often found that most of the enzymes/proteins analyzed are essential, additional criteria have to be implemented for drug target prioritization. Metabolic control analysis (MCA), often in conjunction with kinetic pathway modeling, offers such possibility for prioritization. MCA is a theoretical and experimental approach to analyze how metabolic pathways are controlled. It involves strategies to perform quantitative analyses to determine the degree in which an enzyme controls a pathway flux, a value called flux control coefficient (\( {\mathrm{C}}_{a_i}^J \)). By determining the \( {\mathrm{C}}_{a_i}^J \) of individual steps in a metabolic pathway, the distribution of control of the pathway is established, that is, the identification of the main flux-controlling steps. Therefore, MCA can help in ranking pathway enzymes as drug targets from a metabolic perspective. In this chapter, three approaches to determine \( {\mathrm{C}}_{a_i}^J \) are reviewed: (1) In vitro pathway reconstitution, (2) manipulation of enzyme activities within parasites, and (3) in silico kinetic modeling of the metabolic pathway. To perform these methods, accurate experimental data of enzyme activities, metabolite concentrations and pathway fluxes are necessary. The methodology is illustrated with the example of trypanothione metabolism of Trypanosoma cruzi and protocols to determine such experimental data for this metabolic process are also described. However, the MCA strategy can be applied to any metabolic pathway in the parasite and general directions to perform it are provided in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Gilbert IH (2014) Target-based drug discovery for human African trypanosomiasis: selection of molecular target and chemical matter. Parasitology 141(1):28–36
Field MC, Horn D, Fairlamb AH, Ferguson MAJ, Gray DW, Read KD, De Rycker M, Torrie LS, Wyatt PG, Wyllie S, Gilbert IH (2017) Anti-trypanosomatid drug discovery: an ongoing challenge and a continuing need. Nat Rev Microbiol 15(7):217–231
Glover L, Alsford S, Baker N, Turner DJ, Sanchez-Flores A, Hutchinson S, Hertz-Fowler C, Berriman M, Horn D (2015) Genome-scale RNAi screens for high-throughput phenotyping in bloodstream-form African trypanosomes. Nat Protoc 10(1):106–133
Jones NG, Catta-Preta CMC, Lima APCA, Mottram JC (2018) Genetically validated drug targets in Leishmania: current knowledge and future prospects. ACS Infect Dis 4(4):467–477
Olin-Sandoval V, Moreno-Sánchez R, Saavedra E (2010) Targeting trypanothione metabolism in trypanosomatid human parasites. Curr Drug Targets 11(12):1614–1630
Flohé L (2012) The trypanothione system and the opportunities it offers to create drugs for the neglected kinetoplast diseases. Biotechnol Adv 30(1):294–301
Nelson DL, Cox MM (2008) Lehninger principles of biochemistry, 6th edn. W. H. Freeman, New York, NY, p Chapter 15.2
Moreno-Sanchez R, Saavedra E, Rodriguez-Enriquez S, Olin-Sandoval V (2008) Metabolic control analysis: a tool for designing strategies to manipulate metabolic pathways. J Biomed Biotechnol 2008:597913
Fell D (1997) Understanding the control of metabolism. Portland Press, London, p 301
Bakker BM, Westerhoff HV, Opperdoes FR, Michels PA (2000) Metabolic control analysis of glycolysis in trypanosomes as an approach to improve selectivity and effectiveness of drugs. Mol Biochem Parasitol 106(1):1–10
Saavedra E, Gonzalez-Chavez Z, Moreno-Sanchez R, Michels PAM (2019) Drug target selection for Trypanosoma cruzi metabolism by metabolic control analysis and kinetic modeling. Curr Med Chem 26(36):6652–6671. https://doi.org/10.2174/0929867325666180917104242
Torres NV, Souto R, Meléndez-Hevia E (1989) Study ofthe flux and transition time control coefficient profiles in a metabolic system in vitro and the effect of an external stimulator. Biochem J 260(3):763–769
Giersch C (1995) Determining elasticities from multiple measurements of flux rates and metabolite concentrations. Application of the multiple modulation method to a reconstituted pathway. Eur J Biochem 227(1–2):194–201
Moreno-Sánchez R, Encalada R, Marín-Hernández A, Saavedra E (2008) Experimental validation of metabolic pathway modeling. An illustration with glycolytic segments from Entamoeba histolytica. FEBS J 275(13):3454–3469
González-Chávez Z, Olin-Sandoval V, Rodíguez-Zavala JS, Moreno-Sánchez R, Saavedra E (2015) Metabolic control analysis of the Trypanosoma cruzi peroxide detoxification pathway identifies tryparedoxin as a suitable drug target. Biochem Biophys Acta 1850:263–273
Olin-Sandoval V, González-Chávez Z, Berzunza-Cruz M, Martínez I, Jasso-Chávez R, Becker I, Espinoza B, Moreno-Sánchez R, Saavedra E (2012) Drug target validation of the trypanothione pathway enzymes through metabolic modelling. FEBS J 279(10):1811–1833
González-Chavez Z, Vázquez C, Mejia-Tlachi M, Martínez-Cuevas T, Márquez-Dueñas C, Encalada R, Manning-Cela R, Rodríguez-Enríquez S, PAM M, Moreno-Sánchez R, Saavedra E (2019) Gamma-glutamylcysteine synthetase and tryparedoxin 1 exert high control on the antioxidant system in Trypanosoma cruzi contributing to drug resistance and infectivity. Redox Biol 26:101231
Bruggeman FJ, Westerhoff HV (2007) The nature of systems biology. Trends Microbiol 15(1):45–50
Westerhoff HV (2011) Systems biology left and right. Methods Enzymol 500:3–11
Saa PA, Nielsen LK (2017) Formulation, construction and analysis of kinetic models of metabolism: a review of modelling frameworks. Biotechnol Adv 35(8):981–1003
Haanstra JR, Bakker BM (2015) Drug target identification through systems biology. Drug Discov Today Technol 15:17–22
Comini MA, Dirdjaja N, Kaschel M, Krauth-Siegel RL (2009) Preparative enzymatic synthesis of trypanothione and trypanothione analogues. Int J Parasitol 39:1059–1062
López-Olmos V, Pérez-Nasser N, Piñero D, Ortega E, Hernández R, Espinoza B (1998) Biological characterization and genetic diversity of mexican isolates of Trypanosoma cruzi. Acta Trop 69(3):239–254
Segel IH (1975) Enzyme Kinetics. Wiley, New York, NY
Tummler K, Lubitz T, Schelker M, Klipp E (2014) New types of experimental data shape the use of enzyme kinetics for dynamic network modeling. FEBS J 281(2):549–571
Hoops S, Sahle S, Gauges R, Lee C, Pahle J, Simus N, Singhal M, Xu L, Mendes P, Kummer U (2006) COPASI—a COmplex PAthway SImulator. Bioinformatics 22(24):3067–3074
Vázquez C, Mejia-Tlachi M, González-Chávez Z, Silva A, Rodríguez-Zavala JS, Moreno-Sánchez R, Saavedra E (2017) Buthionine sulfoximine is a multitarget inhibitor of trypanothione synthesis in Trypanosoma cruzi. FEBS Lett 591(23):3881–3894
Taylor MC, Huang H, Kelly JM (2011) Genetic techniques in Trypanosoma cruzi. Adv Microbiol 75:231–250
Flohé L, Steinert P, Hecht JH, Hofmann B (2002) Tryparedoxin and tryparedoxin peroxidase. Methods Enzymol 347:244–258
Acknowledgments
The research in the author’s laboratory is supported by CONACyT grants 272941 and 282663 to E.S. Z.G.-C. was supported by CONACyT Ph.D. fellowship No. 355168 and acknowledges to Programa de Posgrado en Ciencias Bioquímicas of the Universidad Nacional Autónoma de México for academic preparation.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
González-Chávez, Z., Vázquez, C., Moreno-Sánchez, R., Saavedra, E. (2020). Metabolic Control Analysis for Drug Target Prioritization in Trypanosomatids. In: Michels, P., Ginger, M., Zilberstein, D. (eds) Trypanosomatids. Methods in Molecular Biology, vol 2116. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0294-2_41
Download citation
DOI: https://doi.org/10.1007/978-1-0716-0294-2_41
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-0293-5
Online ISBN: 978-1-0716-0294-2
eBook Packages: Springer Protocols