Sass2009 - Approach to an α-synuclein-based BST model of Parkinson's disease

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Model Identifier
BIOMD0000000575
Short description
Sass2009 - Approach to an α-synuclein-based BST model of Parkinson's disease

This model is described in the article:

Sass MB, Lorenz AN, Green RL, Coleman RA.
J. Neurosci. Methods 2009 Apr; 178(2): 366-377

Abstract:

This paper presents a detailed systems model of Parkinson's disease (PD), developed utilizing a pragmatic application of biochemical systems theory (BST) intended to assist experimentalists in the study of system behavior. This approach utilizes relative values as a reasonable initial estimate for BST and provides a theoretical means of applying numerical solutions to qualitative and semi-quantitative understandings of cellular pathways and mechanisms. The approach allows for the simulation of human disease through its ability to organize and integrate existing information about metabolic pathways without having a full quantitative description of those pathways, so that hypotheses about individual processes may be tested in a systems environment. Incorporating this method, the PD model describes alpha-synuclein aggregation as mediated by dopamine metabolism, the ubiquitin-proteasome system, and lysosomal degradation, allowing for the examination of dynamic pathway interactions and the evaluation of possible toxic mechanisms in the aggregation process. Four system perturbations: elevated alpha-synuclein aggregation, impaired dopamine packaging, increased neurotoxins, and alpha-synuclein overexpression, were analyzed for correlation to qualitative PD system hypotheses present in the literature, with the model demonstrating a high level of agreement with these hypotheses. Additionally, various PD treatment methods, including levadopa and monoamine oxidase inhibition (MAOI) therapy, were applied to the disease models to examine their effects on the system. Future additions and refinements to the model may further the understanding of the emergent behaviors of the disease, helping in the identification of system sensitivities and possible therapeutic targets.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Format
SBML (L2V4)
Related Publication
  • A pragmatic approach to biochemical systems theory applied to an alpha-synuclein-based model of Parkinson's disease.
  • Sass MB, Lorenz AN, Green RL, Coleman RA
  • Journal of neuroscience methods , 4/ 2009 , Volume 178 , pages: 366-377 , PubMed ID: 19136028
  • Department of Chemistry, Integrated Science Center, The College of William and Mary, Williamsburg, VA 23187, USA.
  • This paper presents a detailed systems model of Parkinson's disease (PD), developed utilizing a pragmatic application of biochemical systems theory (BST) intended to assist experimentalists in the study of system behavior. This approach utilizes relative values as a reasonable initial estimate for BST and provides a theoretical means of applying numerical solutions to qualitative and semi-quantitative understandings of cellular pathways and mechanisms. The approach allows for the simulation of human disease through its ability to organize and integrate existing information about metabolic pathways without having a full quantitative description of those pathways, so that hypotheses about individual processes may be tested in a systems environment. Incorporating this method, the PD model describes alpha-synuclein aggregation as mediated by dopamine metabolism, the ubiquitin-proteasome system, and lysosomal degradation, allowing for the examination of dynamic pathway interactions and the evaluation of possible toxic mechanisms in the aggregation process. Four system perturbations: elevated alpha-synuclein aggregation, impaired dopamine packaging, increased neurotoxins, and alpha-synuclein overexpression, were analyzed for correlation to qualitative PD system hypotheses present in the literature, with the model demonstrating a high level of agreement with these hypotheses. Additionally, various PD treatment methods, including levadopa and monoamine oxidase inhibition (MAOI) therapy, were applied to the disease models to examine their effects on the system. Future additions and refinements to the model may further the understanding of the emergent behaviors of the disease, helping in the identification of system sensitivities and possible therapeutic targets.
Contributors
Audald Lloret i Villas, administrator

Metadata information

is
BioModels Database MODEL1504130001
BioModels Database BIOMD0000000575
isDescribedBy
PubMed 19136028
hasTaxon
Taxonomy Homo sapiens
hasProperty
Human Disease Ontology Parkinson's disease

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000575_url.xml SBML L2V4 representation of Sass2009 - Approach to an α-synuclein-based BST model of Parkinson\s disease 401.61 KB Preview | Download

Additional files

Sass2009.cps Copasi file of the model 441.57 KB Preview | Download
BIOMD0000000575.m Auto-generated Octave file 41.32 KB Preview | Download
BIOMD0000000575.svg Auto-generated Reaction graph (SVG) 561.51 KB Preview | Download
BIOMD0000000575-biopax3.owl Auto-generated BioPAX (Level 3) 292.68 KB Preview | Download
BIOMD0000000575.sci Auto-generated Scilab file 154.00 bytes Preview | Download
BIOMD0000000575_urn.xml Auto-generated SBML file with URNs 394.84 KB Preview | Download
BIOMD0000000575.xpp Auto-generated XPP file 33.99 KB Preview | Download
BIOMD0000000575.vcml Auto-generated VCML file 900.00 bytes Preview | Download
BIOMD0000000575-biopax2.owl Auto-generated BioPAX (Level 2) 209.72 KB Preview | Download
BIOMD0000000575.pdf Auto-generated PDF file 831.78 KB Preview | Download
BIOMD0000000575.png Auto-generated Reaction graph (PNG) 13.11 MB Preview | Download

  • Model originally submitted by : Audald Lloret i Villas
  • Submitted: 13-Apr-2015 15:55:01
  • Last Modified: 21-Dec-2018 18:13:31
Revisions
  • Version: 3 public model Download this version
    • Submitted on: 21-Dec-2018 18:13:31
    • Submitted by: administrator
    • With comment: Include the additional files provided by the submitter in the original submission: Sass2009.cps
  • Version: 2 public model Download this version
    • Submitted on: 14-Apr-2015 15:38:41
    • Submitted by: Audald Lloret i Villas
    • With comment: Current version of Sass2009 - Approach to an α-synuclein-based BST model of Parkinson's disease
  • Version: 1 public model Download this version
    • Submitted on: 13-Apr-2015 15:55:01
    • Submitted by: Audald Lloret i Villas
    • With comment: Original import of Sass2009 - Approach to an α-synuclein-based BST model of Parkinson's disease
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
Lewy body

Alpha-synuclein ; Lewy body
0.01 dimensionless
Dopamine

dopamine
2.0 dimensionless
Neuromelanin

5,6-dihydroxyindole ; polymer
1.0 dimensionless
Alpha synuclein

Alpha-synuclein
0.2 dimensionless
Neurotoxins

neurotoxin
0.01 dimensionless
Bioamines

amine ; biological role
0.1 dimensionless
O2

dioxygen
2.0 dimensionless
Reactions
Reactions Rate Parameters
(Lewy_body + Preautophagosome_membrane) => (Autophagosome)

([Alpha-synuclein; Lewy body] + [autophagosome membrane]) => ([autophagosome])
k53*Lewy_body^g534*Preautophagosome_membrane^g5380

k53*[Alpha-synuclein; Lewy body]^g534*[autophagosome membrane]^g5380
g5380 = 1.0; g534 = 1.0; k53 = 0.05
(L-Dopa) => (Dopamine + CO2)

([L-dopa]) => ([dopamine] + [carbon dioxide])
Neuronal_cytosol*k14*L_Dopa^g1437*DDC^g1467

Neuronal_cytosol*k14*[L-dopa]^g1437*[Aromatic-L-amino-acid decarboxylase]^g1467
k14 = 3.0; g1467 = 1.0; g1437 = 1.0
(Dopamine + Vesicle) => (V-DA)

([dopamine] + [vesicle]) => ([dopamine])
k15*Dopamine^g156*Vesicle_0^g1544*VMAT2^g1545

k15*[dopamine]^g156*[vesicle]^g1544*[Synaptic vesicular amine transporter]^g1545
g156 = 1.0; k15 = 0.2; g1545 = 1.0; g1544 = 1.0
(L-Dopa + O2 + Cysteine) => (Neuromelanin + H2O2 + CO2)

([L-dopa] + [dioxygen] + [cysteine]) => ([5,6-dihydroxyindole; polymer] + [hydrogen peroxide] + [carbon dioxide])
Neuronal_cytosol*k100*L_Dopa^g10037*O2_0^g10051*Cysteine^g100115

Neuronal_cytosol*k100*[L-dopa]^g10037*[dioxygen]^g10051*[cysteine]^g100115
g10051 = 1.0; g100115 = 1.0; g10037 = 1.0; k100 = 0.005
(L-Tyr + O2 + Cysteine) => (Neuromelanin + H2O2 + CO2)

([L-tyrosine] + [dioxygen] + [cysteine]) => ([5,6-dihydroxyindole; polymer] + [hydrogen peroxide] + [carbon dioxide])
Neuronal_cytosol*k101*L_Tyr^g10136*O2_0^g10151*Cysteine^g101115

Neuronal_cytosol*k101*[L-tyrosine]^g10136*[dioxygen]^g10151*[cysteine]^g101115
k101 = 0.005; g101115 = 1.0; g10151 = 1.0; g10136 = 1.0
(DA_quinone + O2 + Cysteine) => (Neuromelanin + CO2)

([dopamine; quinone] + [dioxygen] + [cysteine]) => ([5,6-dihydroxyindole; polymer] + [carbon dioxide])
Neuronal_cytosol*k102*DA_quinone^g10210*O2_0^g10251*Cysteine^g102115

Neuronal_cytosol*k102*[dopamine; quinone]^g10210*[dioxygen]^g10251*[cysteine]^g102115
g10251 = 1.0; g10210 = 1.0; k102 = 0.005; g102115 = 1.0
(Fe3+ + Neuromelanin) => (Neuromelanin-ntox-Fe3+)

([iron(3+)] + [5,6-dihydroxyindole; polymer]) => ([polymer; 5,6-dihydroxyindole; iron(3+); neurotoxin])
Neuronal_cytosol*k115*Fe3^g11565*Neuromelanin^g115118

Neuronal_cytosol*k115*[iron(3+)]^g11565*[5,6-dihydroxyindole; polymer]^g115118
g115118 = 1.0; g11565 = 1.0; k115 = 0.5
(Alpha_synuclein + Hsc70) => (Hsc70-asyn)

([Alpha-synuclein] + [Heat shock cognate 71 kDa protein]) => ([Alpha-synuclein; Heat shock cognate 71 kDa protein])
Neuronal_cytosol*k43*Alpha_synuclein^g431*Hsc70^g4384

Neuronal_cytosol*k43*[Alpha-synuclein]^g431*[Heat shock cognate 71 kDa protein]^g4384
k43 = 0.05; g431 = 1.0; g4384 = 1.0
(Alpha_synuclein + Preautophagosome_membrane) => (Autophagosome)

([Alpha-synuclein] + [autophagosome membrane]) => ([autophagosome])
k50*Alpha_synuclein^g501*Preautophagosome_membrane^g5080

k50*[Alpha-synuclein]^g501*[autophagosome membrane]^g5080
g501 = 1.0; g5080 = 1.0; k50 = 0.05
(Neuromelanin + Neurotoxins) => (Neuromelanin-ntox-Fe3+)

([5,6-dihydroxyindole; polymer] + [neurotoxin]) => ([polymer; 5,6-dihydroxyindole; iron(3+); neurotoxin])
Neuronal_cytosol*k116*Neuromelanin^g116118*Neurotoxins^g11642

Neuronal_cytosol*k116*[5,6-dihydroxyindole; polymer]^g116118*[neurotoxin]^g11642
k116 = 0.5; g11642 = 1.0; g116118 = 1.0
(Bioamines + Vesicle) => (V-ntox-ba)

([amine; biological role] + [vesicle]) => ([neurotoxin; amine; biological role])
k16*Bioamines^g1643*Vesicle_0^g1644

k16*[amine; biological role]^g1643*[vesicle]^g1644
k16 = 1.0E-4; g1644 = 1.0; g1643 = 1.0
(Dopamine + O2) => (DA_quinone + O2-)

([dopamine] + [dioxygen]) => ([dopamine; quinone] + [superoxide])
Neuronal_cytosol*k18*Dopamine^g186*O2_0^g1851

Neuronal_cytosol*k18*[dopamine]^g186*[dioxygen]^g1851
k18 = 0.02; g186 = 1.0; g1851 = 1.0
(Dopamine + O2 + H2O) => (NH3 + DOPAL + H2O2)

([dopamine] + [dioxygen] + [water]) => ([ammonia] + [3,4-dihydroxyphenylacetaldehyde] + [hydrogen peroxide])
Neuronal_cytosol*k19*Dopamine^g196*O2_0^g1951*H2O^g1960*MAO^g1953

Neuronal_cytosol*k19*[dopamine]^g196*[dioxygen]^g1951*[water]^g1960*[Amine oxidase [flavin-containing] A]^g1953
g1960 = 1.0; g196 = 1.0; k19 = 0.01; g1953 = 1.0; g1951 = 1.0
(H2O2) => (H2O + O2)

([hydrogen peroxide]) => ([water] + [dioxygen])
Neuronal_cytosol*k22*H2O2^g229*Catalase^g2259

Neuronal_cytosol*k22*[hydrogen peroxide]^g229*[Catalase]^g2259
g2259 = 1.0; g229 = 1.0; k22 = 0.5
(O2-) => (H2O2 + O2)

([superoxide]) => ([hydrogen peroxide] + [dioxygen])
Neuronal_cytosol*k56*O2^g5686*SOD^g5687

Neuronal_cytosol*k56*[superoxide]^g5686*[Superoxide dismutase [Cu-Zn]]^g5687
g5687 = 1.0; g5686 = 1.0; k56 = 0.05
Curator's comment:
(added: 14 Apr 2015, 12:09:56, updated: 14 Apr 2015, 12:09:56)
Figure 15 of the reference publication has been reproduced here. Dynamics of protofibrils, fibrils and Lewy bodies are plotted over 100 time units. This figure displays a percentage comparison of a disease model, where levels of α-synuclein in the system are increased by 10%, and the baseline model. (i.e. α-synuclein increases to 0,22 at disease model). For the sake of simulation, data from both models (disease and baseline) was merged. Subsequently, the disease model was divided by the baseline model and percentage format was applied. The simulation was done using Copasi v4.14 (Build 89) and the plot was generated using Gnuplot. The Copasi file of the baseline model with simulation settings can be downloaded from the below link: