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research
Mathematical modelling of polyamine metabolism in bloodstream-form trypanosoma brucei: An application to drug target identification
Authors
AE Pegg
AH Fairlamb
+53Β more
AJ Bitonti
AJ Bitonti
Andrew R. Dalby
B Goldberg
BJ Berger
C Rodriguez-Caso
CJ Bacchi
CJ Bacchi
CJ Bacchi
CJ Bacchi
CW Porter
David Gilbert
David Reid
Desmond J. Higham
ED Sontag
EK Willert
EK Willert
F Checchi
G Priotto
H Kitano
IM Vincent
JF Turrens
JR Sufrin
JR Sufrin
K Kaur
L Birnbaumer
L Christa
L Ljung
LY Ghoda
M Duszenko
MC Taylor
MK Riscoe
MR Ariyanayagam
MR Ariyanayagam
N Yarlett
N Yarlett
N Yarlett
NAW van Riel
NAW van Riel
O Erez
O Heby
PK Fyfe
RM Reguera
S Muller
S Peter
SL Oza
SL Oza
T Suzuki
TC Beswick
V Bellofatto
V Olin-Sandoval
Xu Gu
Y Xiao
Publication date
1 January 2013
Publisher
'Public Library of Science (PLoS)'
Doi
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on
PubMed
Abstract
Β© 2013 Gu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedThis article has been made available through the Brunel Open Access Publishing Fund.We present the first computational kinetic model of polyamine metabolism in bloodstream-form Trypanosoma brucei, the causative agent of human African trypanosomiasis. We systematically extracted the polyamine pathway from the complete metabolic network while still maintaining the predictive capability of the pathway. The kinetic model is constructed on the basis of information gleaned from the experimental biology literature and defined as a set of ordinary differential equations. We applied Michaelis-Menten kinetics featuring regulatory factors to describe enzymatic activities that are well defined. Uncharacterised enzyme kinetics were approximated and justified with available physiological properties of the system. Optimisation-based dynamic simulations were performed to train the model with experimental data and inconsistent predictions prompted an iterative procedure of model refinement. Good agreement between simulation results and measured data reported in various experimental conditions shows that the model has good applicability in spite of there being gaps in the required data. With this kinetic model, the relative importance of the individual pathway enzymes was assessed. We observed that, at low-to-moderate levels of inhibition, enzymes catalysing reactions of de novo AdoMet (MAT) and ornithine production (OrnPt) have more efficient inhibitory effect on total trypanothione content in comparison to other enzymes in the pathway. In our model, prozyme and TSHSyn (the production catalyst of total trypanothione) were also found to exhibit potent control on total trypanothione content but only when they were strongly inhibited. Different chemotherapeutic strategies against T. brucei were investigated using this model and interruption of polyamine synthesis via joint inhibition of MAT or OrnPt together with other polyamine enzymes was identified as an optimal therapeutic strategy.The work was carried out under a PhD programme partly funded by Prof. Ray Welland, School of Computing Science, University of Glasgo
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