Salcedo-Sora2016 - Microbial folate biosynthesis and utilisation

This model is described in the article:
Abstract:
The metabolic biochemistry of folate biosynthesis and utilisation has evolved into a complex network of reactions. Although this complexity represents challenges to the field of folate research it has also provided a renewed source for antimetabolite targets. A range of improved folate chemotherapy continues to be developed and applied particularly to cancer and chronic inflammatory diseases. However, new or better antifolates against infectious diseases remain much more elusive. In this paper we describe the assembly of a generic deterministic mathematical model of microbial folate metabolism. Our aim is to explore how a mathematical model could be used to explore the dynamics of this inherently complex set of biochemical reactions. Using the model it was found that: (1) a particular small set of folate intermediates are overrepresented, (2) inhibitory profiles can be quantified by the level of key folate products, (3) using the model to scan for the most effective combinatorial inhibitions of folate enzymes we identified specific targets which could complement current antifolates, and (4) the model substantiates the case for a substrate cycle in the folinic acid biosynthesis reaction. Our model is coded in the systems biology markup language and has been deposited in the BioModels Database (MODEL1511020000), this makes it accessible to the community as a whole.
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A mathematical model of microbial folate biosynthesis and utilisation: implications for antifolate development.
- Salcedo-Sora JE
- Molecular bioSystems , 3/ 2016 , Volume 12 , pages: 923-933 , PubMed ID: 26794619
- School of Health Science, Liverpool Hope University, Hope Park, Liverpool, L16 9JD, UK. salcede@hope.a.uk.
- The metabolic biochemistry of folate biosynthesis and utilisation has evolved into a complex network of reactions. Although this complexity represents challenges to the field of folate research it has also provided a renewed source for antimetabolite targets. A range of improved folate chemotherapy continues to be developed and applied particularly to cancer and chronic inflammatory diseases. However, new or better antifolates against infectious diseases remain much more elusive. In this paper we describe the assembly of a generic deterministic mathematical model of microbial folate metabolism. Our aim is to explore how a mathematical model could be used to explore the dynamics of this inherently complex set of biochemical reactions. Using the model it was found that: (1) a particular small set of folate intermediates are overrepresented, (2) inhibitory profiles can be quantified by the level of key folate products, (3) using the model to scan for the most effective combinatorial inhibitions of folate enzymes we identified specific targets which could complement current antifolates, and (4) the model substantiates the case for a substrate cycle in the folinic acid biosynthesis reaction. Our model is coded in the systems biology markup language and has been deposited in the BioModels Database (MODEL1511020000), this makes it accessible to the community as a whole.
Submitter of this revision: Sarubini Kananathan
Modellers: J. Enrique Salcedo-Sora, Sarubini Kananathan
Metadata information
BioModels Database MODEL1511020000
BioModels Database BIOMD0000000725
hasProperty (5 statements)
Experimental Factor Ontology infectious disease
NCIt Folate Biosynthesis Pathway
NCIt Microorganism
Pathway Ontology shikimate metabolic pathway
isDescribedBy (1 statement)
Connected external resources
Name | Description | Size | Actions |
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Model files |
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Model.xml | SBML L2V4 representation of Salcedo-Sora2016 - Microbial folate biosynthesis and utilisation | 204.69 KB | Preview | Download |
Additional files |
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MODEL1511020000.pdf | Auto-generated PDF file | 406.69 KB | Preview | Download |
MODEL1511020000.png | Auto-generated Reaction graph (PNG) | 1.26 MB | Preview | Download |
MODEL1511020000.sci | Auto-generated Scilab file | 15.89 KB | Preview | Download |
MODEL1511020000.svg | Auto-generated Reaction graph (SVG) | 122.10 KB | Preview | Download |
MODEL1511020000.vcml | Auto-generated VCML file | 176.64 KB | Preview | Download |
MODEL1511020000_urn.xml | Auto-generated SBML file with URNs | 167.02 KB | Preview | Download |
- Model originally submitted by : J. Enrique Salcedo-Sora
- Submitted: Nov 2, 2015 2:19:42 PM
- Last Modified: Dec 5, 2018 11:01:18 AM
Revisions
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Version: 4
- Submitted on: Dec 5, 2018 11:01:18 AM
- Submitted by: Sarubini Kananathan
- With comment: Automatically added model identifier BIOMD0000000725
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Version: 2
- Submitted on: Feb 10, 2016 11:20:53 AM
- Submitted by: J. Enrique Salcedo-Sora
- With comment: Current version of Salcedo-Sora2016 - Microbial folate biosynthesis and utilisation
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Version: 1
- Submitted on: Nov 2, 2015 2:19:42 PM
- Submitted by: J. Enrique Salcedo-Sora
- With comment: Original import of New Model
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: Variable used inside SBML models
Species | Initial Concentration/Amount |
---|---|
Pi Orthophosphate |
2.725541316 μmol |
CM Chorismate |
1.009195849 μmol |
meTHFGlu 5,10-Methenyltetrahydrofolate |
0.9082384182 μmol |
COTwo | 0.988683328 μmol |
ATP ATP |
963.0188351 μmol |
DHQ 3-Dehydroquinate |
0.9994087764 μmol |
AHMDPP 6-Hydroxymethyl-7,8-dihydropterin diphosphate |
0.9873083466 μmol |
THFGlu THF-polyglutamate |
1.0 μmol |
Reactions | Rate | Parameters |
---|---|---|
DHP + Glu + ATP => DHF + ADP + Pi; DHP, Glu, ATP | compartment*vmax*DHP*Glu*ATP/(kdhp*kglu*katp+kdhp*(Glu+ATP)+kglu*(DHP+ATP)+katp*(Glu+ATP)+DHP*Glu*ATP) | vmax=2.821; kglu=1380.0; katp=100.0; kdhp=1.0 |
AHMDPP + pABA => DHP + Pi; AHMDPP, pABA | compartment*vmax*AHMDPP*pABA/(kahmdpp*kpaba+kpaba*AHMDPP+kahmdpp*pABA+AHMDPP*pABA) | kpaba=2.6; vmax=105.014; kahmdpp=3.15 |
CVPSK => CM + Pi; CVPSK | compartment*V*CVPSK/(Km+CVPSK) | Km=12.7; V=728.0 |
ATP + ffTHFGlu => ADP + Pi + meTHFGlu; ATP, ffTHFGlu | compartment*vmax*ATP*ffTHFGlu/(katp*kffthfglu+katp*ffTHFGlu+kffthfglu*ATP+ATP*ffTHFGlu) | kffthfglu=5.0; katp=50.0; vmax=500.0 |
DLp + Gly => SAmDLp + COTwo; DLp, Gly | compartment*vmax*DLp*Gly/(kgly*kdlp+kgly*Gly+kdlp*DLp+DLp*Gly) | kdlp=290.0; kgly=4505.0; vmax=751.66 |
THF + Glu + ATP => THFGlu + ADP + Pi; DHF, THF, Glu, ATP | compartment*vmax*THF*Glu*ATP/(kthf*(1+DHF/kidhf)*kglu*katp+kthf*(Glu+ATP)+kglu*(THF+ATP)+katp*(THF+Glu)+THF*Glu*ATP) | kthf=26.0; vmax=84.63; kglu=740.0; katp=128.0; kidhf=3.1 |
SKP + PEP => CVPSK + Pi; SKP, PEP | compartment*vmax*SKP*PEP/(kpep*kskp+kpep*PEP+kskp*SKP+PEP*SKP) | kpep=93.0; kskp=80.0; vmax=1547.0 |
DAHP => DHQ + Pi; DAHP | compartment*V*DAHP/(Km+DAHP) | Km=4.7; V=7.462 |
fTHFGlu + ADP + Pi => THFGlu + ATP + Formyl; fTHFGlu, ADP, Pi | compartment*vmax*fTHFGlu*ADP*Pi/(kthfglu*kformyl*katp+kthfglu*(ADP+Pi)+kformyl*(fTHFGlu+Pi)+katp*(ADP+fTHFGlu)+fTHFGlu*ADP*Pi) | vmax=15315.3; kformyl=3190.0; kthfglu=134.0; katp=74.5 |
(added: 05 Dec 2018, 11:00:38, updated: 05 Dec 2018, 11:00:38)