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Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application

Mycobacterium tuberculosis(Mtu), a successful pathogen, has developed resistance against the existing anti-tubercular drugs necessitating discovery of drugs with novel action. Enzymes involved in peptidoglycan biosynthesis are attractive targets for antibacterial drug discovery. The bifunctional enz...

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Autores principales: Singh, Vivek K., Das, Kaveri, Seshadri, Kothandaraman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428340/
https://www.ncbi.nlm.nih.gov/pubmed/22952829
http://dx.doi.org/10.1371/journal.pone.0043969
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author Singh, Vivek K.
Das, Kaveri
Seshadri, Kothandaraman
author_facet Singh, Vivek K.
Das, Kaveri
Seshadri, Kothandaraman
author_sort Singh, Vivek K.
collection PubMed
description Mycobacterium tuberculosis(Mtu), a successful pathogen, has developed resistance against the existing anti-tubercular drugs necessitating discovery of drugs with novel action. Enzymes involved in peptidoglycan biosynthesis are attractive targets for antibacterial drug discovery. The bifunctional enzyme mycobacterial GlmU (Glucosamine 1-phosphate N-acetyltransferase/ N-acetylglucosamine-1-phosphate uridyltransferase) has been a target enzyme for drug discovery. Its C- and N- terminal domains catalyze acetyltransferase (rxn-1) and uridyltransferase (rxn-2) activities respectively and the final product is involved in peptidoglycan synthesis. However, the bifunctional nature of GlmU poses difficulty in deciding which function to be intervened for therapeutic advantage. Genetic analysis showed this as an essential gene but it is still unclear whether any one or both of the activities are critical for cell survival. Often enzymatic activity with suitable high-throughput assay is chosen for random screening, which may not be the appropriate biological function inhibited for maximal effect. Prediction of rate-limiting function by dynamic network analysis of reactions could be an option to identify the appropriate function. With a view to provide insights into biochemical assays with appropriate activity for inhibitor screening, kinetic modelling studies on GlmU were undertaken. Kinetic model of Mtu GlmU-catalyzed reactions was built based on the available kinetic data on Mtu and deduction from Escherichia coli data. Several model variants were constructed including coupled/decoupled, varying metabolite concentrations and presence/absence of product inhibitions. This study demonstrates that in coupled model at low metabolite concentrations, inhibition of either of the GlmU reactions cause significant decrement in the overall GlmU rate. However at higher metabolite concentrations, rxn-2 showed higher decrement. Moreover, with available intracellular concentration of the metabolites and in vivo variant of model, uncompetitive inhibition of rxn-2 caused highest decrement. Thus, at physiologically relevant metabolite concentrations, targeting uridyltranferase activity of Mtu GlmU would be a better choice for therapeutic intervention.
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spelling pubmed-34283402012-09-05 Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application Singh, Vivek K. Das, Kaveri Seshadri, Kothandaraman PLoS One Research Article Mycobacterium tuberculosis(Mtu), a successful pathogen, has developed resistance against the existing anti-tubercular drugs necessitating discovery of drugs with novel action. Enzymes involved in peptidoglycan biosynthesis are attractive targets for antibacterial drug discovery. The bifunctional enzyme mycobacterial GlmU (Glucosamine 1-phosphate N-acetyltransferase/ N-acetylglucosamine-1-phosphate uridyltransferase) has been a target enzyme for drug discovery. Its C- and N- terminal domains catalyze acetyltransferase (rxn-1) and uridyltransferase (rxn-2) activities respectively and the final product is involved in peptidoglycan synthesis. However, the bifunctional nature of GlmU poses difficulty in deciding which function to be intervened for therapeutic advantage. Genetic analysis showed this as an essential gene but it is still unclear whether any one or both of the activities are critical for cell survival. Often enzymatic activity with suitable high-throughput assay is chosen for random screening, which may not be the appropriate biological function inhibited for maximal effect. Prediction of rate-limiting function by dynamic network analysis of reactions could be an option to identify the appropriate function. With a view to provide insights into biochemical assays with appropriate activity for inhibitor screening, kinetic modelling studies on GlmU were undertaken. Kinetic model of Mtu GlmU-catalyzed reactions was built based on the available kinetic data on Mtu and deduction from Escherichia coli data. Several model variants were constructed including coupled/decoupled, varying metabolite concentrations and presence/absence of product inhibitions. This study demonstrates that in coupled model at low metabolite concentrations, inhibition of either of the GlmU reactions cause significant decrement in the overall GlmU rate. However at higher metabolite concentrations, rxn-2 showed higher decrement. Moreover, with available intracellular concentration of the metabolites and in vivo variant of model, uncompetitive inhibition of rxn-2 caused highest decrement. Thus, at physiologically relevant metabolite concentrations, targeting uridyltranferase activity of Mtu GlmU would be a better choice for therapeutic intervention. Public Library of Science 2012-08-27 /pmc/articles/PMC3428340/ /pubmed/22952829 http://dx.doi.org/10.1371/journal.pone.0043969 Text en © 2012 Singh et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
Singh, Vivek K.
Das, Kaveri
Seshadri, Kothandaraman
Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title_full Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title_fullStr Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title_full_unstemmed Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title_short Kinetic Modelling of GlmU Reactions – Prioritization of Reaction for Therapeutic Application
title_sort kinetic modelling of glmu reactions – prioritization of reaction for therapeutic application
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428340/
https://www.ncbi.nlm.nih.gov/pubmed/22952829
http://dx.doi.org/10.1371/journal.pone.0043969
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