Singh2006_TCA_Ecoli_glucose

This a model from the article:
Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drugtargets.
Singh VK , Ghosh I Theor Biol Med Model
2006 Aug 3;3:27 16887020
,
Abstract:
BACKGROUND: Targeting persistent tubercule bacilli has become an important challenge in the development of anti-tuberculous drugs. As the glyoxylate bypass is essential for persistent bacilli, interference with it holds the potential for designing new antibacterial drugs. We have developed kinetic models of the tricarboxylic acid cycle and glyoxylate bypass in Escherichia coli and Mycobacterium tuberculosis, and studied the effects of inhibition of various enzymes in the M. tuberculosis model. RESULTS: We used E. coli to validate the pathway-modeling protocol and showed that changes in metabolic flux can be estimated from gene expression data. The M. tuberculosis model reproduced the observation that deletion of one of the two isocitrate lyase genes has little effect on bacterial growth in macrophages, but deletion of both genes leads to the elimination of the bacilli from the lungs. It also substantiated the inhibition of isocitrate lyases by 3-nitropropionate. On the basis of our simulation studies, we propose that: (i) fractional inactivation of both isocitrate dehydrogenase 1 and isocitrate dehydrogenase 2 is required for a flux through the glyoxylate bypass in persistent mycobacteria; and (ii) increasing the amountof active isocitrate dehydrogenases can stop the flux through the glyoxylate bypass, so the kinase that inactivates isocitrate dehydrogenase 1 and/or the proposed inactivator of isocitrate dehydrogenase 2 is a potential target for drugs against persistent mycobacteria. In addition, competitive inhibition of isocitrate lyases along with a reduction in the inactivation of isocitrate dehydrogenases appears to be a feasible strategy for targeting persistent mycobacteria. CONCLUSION: We used kinetic modeling of biochemical pathways to assess various potential anti-tuberculous drug targets that interfere with the glyoxylate bypass flux, and indicated the type of inhibition needed to eliminate the pathogen. The advantage of such an approach to the assessment of drug targets is that it facilitates the study of systemic effect(s) of the modulation of the target enzyme(s) in the cellular environment.
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To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets.
- Singh VK, Ghosh I
- Theoretical biology & medical modelling , 0/ 2006 , Volume 3 , pages: 27 , PubMed ID: 16887020
- Bioinformatics Centre, University of Pune, Pune-411007, India. vivek@bioinfo.ernet.in
- BACKGROUND: Targeting persistent tubercule bacilli has become an important challenge in the development of anti-tuberculous drugs. As the glyoxylate bypass is essential for persistent bacilli, interference with it holds the potential for designing new antibacterial drugs. We have developed kinetic models of the tricarboxylic acid cycle and glyoxylate bypass in Escherichia coli and Mycobacterium tuberculosis, and studied the effects of inhibition of various enzymes in the M. tuberculosis model. RESULTS: We used E. coli to validate the pathway-modeling protocol and showed that changes in metabolic flux can be estimated from gene expression data. The M. tuberculosis model reproduced the observation that deletion of one of the two isocitrate lyase genes has little effect on bacterial growth in macrophages, but deletion of both genes leads to the elimination of the bacilli from the lungs. It also substantiated the inhibition of isocitrate lyases by 3-nitropropionate. On the basis of our simulation studies, we propose that: (i) fractional inactivation of both isocitrate dehydrogenase 1 and isocitrate dehydrogenase 2 is required for a flux through the glyoxylate bypass in persistent mycobacteria; and (ii) increasing the amount of active isocitrate dehydrogenases can stop the flux through the glyoxylate bypass, so the kinase that inactivates isocitrate dehydrogenase 1 and/or the proposed inactivator of isocitrate dehydrogenase 2 is a potential target for drugs against persistent mycobacteria. In addition, competitive inhibition of isocitrate lyases along with a reduction in the inactivation of isocitrate dehydrogenases appears to be a feasible strategy for targeting persistent mycobacteria. CONCLUSION: We used kinetic modeling of biochemical pathways to assess various potential anti-tuberculous drug targets that interfere with the glyoxylate bypass flux, and indicated the type of inhibition needed to eliminate the pathogen. The advantage of such an approach to the assessment of drug targets is that it facilitates the study of systemic effect(s) of the modulation of the target enzyme(s) in the cellular environment.
Metadata information
Name | Description | Size | Actions |
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Model files |
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BIOMD0000000222_url.xml | SBML L2V4 representation of Singh2006_TCA_Ecoli_glucose | 46.59 KB | Preview | Download |
Additional files |
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BIOMD0000000222_manual.png | Manually generated Reaction graph (PNG) | 15.47 KB | Preview | Download |
BIOMD0000000222_manual.svg | Manually generated Reaction graph (SVG) | 30.60 KB | Preview | Download |
BIOMD0000000222.vcml | Auto-generated VCML file | 50.80 KB | Preview | Download |
BIOMD0000000222_urn.xml | Auto-generated SBML file with URNs | 48.79 KB | Preview | Download |
BIOMD0000000222.pdf | Auto-generated PDF file | 197.67 KB | Preview | Download |
BIOMD0000000222.sci | Auto-generated Scilab file | 159.00 Bytes | Preview | Download |
BIOMD0000000222.m | Auto-generated Octave file | 10.61 KB | Preview | Download |
BIOMD0000000222-biopax2.owl | Auto-generated BioPAX (Level 2) | 27.05 KB | Preview | Download |
BIOMD0000000222-biopax3.owl | Auto-generated BioPAX (Level 3) | 37.68 KB | Preview | Download |
BIOMD0000000222.svg | Auto-generated Reaction graph (SVG) | 30.60 KB | Preview | Download |
BIOMD0000000222.png | Auto-generated Reaction graph (PNG) | 15.47 KB | Preview | Download |
BIOMD0000000222.xpp | Auto-generated XPP file | 6.99 KB | Preview | Download |
- Model originally submitted by : Indira Ghosh
- Submitted: Sep 29, 2006 11:47:42 PM
- Last Modified: Dec 20, 2010 9:47:18 AM
Revisions
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Version: 2
- Submitted on: Dec 20, 2010 9:47:18 AM
- Submitted by: Indira Ghosh
- With comment: Current version of Singh2006_TCA_Ecoli_glucose
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Version: 1
- Submitted on: Sep 29, 2006 11:47:42 PM
- Submitted by: Indira Ghosh
- With comment: Original import of Singh_Ghosh2006_TCA_eco_glucose
(*) You might be seeing discontinuous
revisions as only public revisions are displayed here. Any private revisions
of this model will only be shown to the submitter and their collaborators.
: Variable used inside SBML models
Species | Initial Concentration/Amount |
---|---|
icit isocitric acid ; Isocitrate |
0.018 mmol |
akg 2-oxoglutaric acid ; 2-Oxoglutarate |
0.2 mmol |
sca succinyl-CoA ; Succinyl-CoA |
0.04 mmol |
suc succinic acid ; Succinate |
0.6 mmol |
fa fumaric acid ; Fumarate |
0.3 mmol |
aca acetyl-CoA ; Acetyl-CoA |
0.5 mmol |
oaa oxaloacetic acid ; Oxaloacetate |
0.004 mmol |
coa coenzyme A ; C000010 |
1.0E-4 mmol |
Reactions | Rate | Parameters |
---|---|---|
cit => icit | cell*(Vf_acn*cit/Kcit_acn-Vr_acn*icit/Kicit_acn)/(1+cit/Kcit_acn+icit/Kicit_acn) | Kicit_acn=3.33 mM; Vr_acn=0.912 mM_per_min; Kcit_acn=1.7 mM; Vf_acn=91.2 mM_per_min |
icit => akg | cell*(Vf_icd*icit/Kicit_icd-Vr_icd*akg/Kakg_icd)/(1+icit/Kicit_icd+akg/Kakg_icd) | Kakg_icd=0.13 mM; Kicit_icd=0.008 mM; Vr_icd=0.1472 mM_per_min; Vf_icd=14.72 mM_per_min |
akg => sca | cell*(Vf_kdh*akg/Kakg_kdh-Vr_kdh*sca/Ksca_kdh)/(1+akg/Kakg_kdh+sca/Ksca_kdh) | Kakg_kdh=0.1 mM; Vr_kdh=0.3584 mM_per_min; Vf_kdh=35.84 mM_per_min; Ksca_kdh=1.0 mM |
akg => biosyn; icit | cell*0.188*(Vf_icd*icit/Kicit_icd-Vr_icd*akg/Kakg_icd)/(1+icit/Kicit_icd+akg/Kakg_icd) | Kakg_icd=0.13 mM; Kicit_icd=0.008 mM; Vr_icd=0.1472 mM_per_min; Vf_icd=14.72 mM_per_min |
sca => suc | cell*(Vf_scas*sca/Ksca_scas-Vr_scas*suc/Ksuc_scas)/(1+sca/Ksca_scas+suc/Ksuc_scas) | Vf_scas=3.5 mM_per_min; Ksca_scas=0.02 mM; Vr_scas=0.035 mM_per_min; Ksuc_scas=5.0 mM |
suc => fa | cell*(Vf_sdh*suc/Ksuc_sdh-Vr_sdh*fa/Kfa_sdh)/(1+suc/Ksuc_sdh+fa/Kfa_sdh) | Vr_sdh=7.31 mM_per_min; Vf_sdh=7.38 mM_per_min; Ksuc_sdh=0.02 mM; Kfa_sdh=0.4 mM |
icit => suc + gly | cell*(Vf_icl*icit/Kicit_icl-Vr_icl*suc/Ksuc_icl*gly/Kgly_icl)/(1+icit/Kicit_icl+suc/Ksuc_icl+gly/Kgly_icl+icit/Kicit_icl*suc/Ksuc_icl+suc/Ksuc_icl*gly/Kgly_icl) | Ksuc_icl=0.59 mM; Kgly_icl=0.13 mM; Vf_icl=1.9 mM_per_min; Vr_icl=0.019 mM_per_min; Kicit_icl=0.604 mM |
aca + oaa => coa + cit | cell*(Vf_cs*aca/Kaca_cs*oaa/Koaa_cs-Vr_cs*coa/Kcoa_cs*cit/Kcit_cs)/((1+aca/Kaca_cs+coa/Kcoa_cs)*(1+oaa/Koaa_cs+cit/Kcit_cs)) | Kaca_cs=0.03 mM; Kcit_cs=0.7 mM; Vf_cs=91.2 mM_per_min; Koaa_cs=0.07 mM; Kcoa_cs=0.3 mM; Vr_cs=0.912 mM_per_min |
gly + aca => mal + coa | cell*(Vf_ms*gly/Kgly_ms*aca/Kaca_ms-Vr_ms*mal/Kmal_ms*coa/Kcoa_ms)/((1+gly/Kgly_ms+mal/Kmal_ms)*(1+aca/Kaca_ms+coa/Kcoa_ms)) | Kmal_ms=1.0 mM; Vf_ms=1.9 mM_per_min; Vr_ms=0.019 mM_per_min; Kgly_ms=2.0 mM; Kcoa_ms=0.1 mM; Kaca_ms=0.01 mM |
mal => oaa | cell*(Vf_mdh*mal/Kmal_mdh-Vr_mdh*oaa/Koaa_mdh)/(1+mal/Kmal_mdh+oaa/Koaa_mdh) | Koaa_mdh=0.04 mM; Kmal_mdh=2.6 mM; Vr_mdh=353.11 mM_per_min; Vf_mdh=356.64 mM_per_min |
(added: 07 Jul 2009, 16:17:50, updated: 07 Jul 2009, 16:17:50)