Dataset Information

Sneppen2009 - Modeling proteasome dynamics in Parkinson's disease

ABSTRACT: Sneppen2009 - Modeling proteasome dynamics in Parkinson's disease This model is described in the article: Modeling proteasome dynamics in Parkinson's disease. Sneppen K, Lizana L, Jensen MH, Pigolotti S, Otzen D. Phys Biol 2009; 6(3): 036005 Abstract: In Parkinson's disease (PD), there is evidence that alpha-synuclein (alphaSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin-proteasome system. Here, we develop a simple dynamical model for the on-going conflict between alphaSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature alphaSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the alphaSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system. This model is hosted on BioModels Database and identified by: BIOMD0000000548. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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.

DISEASE(S): Parkinson's Disease

SUBMITTER: Audald Lloret i Villas

PROVIDER: BIOMD0000000548 | BioModels | 2014-09-10

REPOSITORIES: BioModels

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Publications

Modeling proteasome dynamics in Parkinson's disease.

Sneppen Kim K Lizana Ludvig L Jensen Mogens H MH Pigolotti Simone S Otzen Daniel D

Physical biology 20090501 3

In Parkinson's disease (PD), there is evidence that alpha-synuclein (alphaSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin-proteasome system. Here, we develop a simple dynamical model for the on-going conflict between alphaSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature alphaSN fibrils and their protofilament precu ...[more]

PMID: 19411740

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Project description:Kuznetsov2016(II) - α-syn aggregation kinetics in Parkinson's This theoretical model uses 2-step Finke-Watzky (FW) kinetics todescribe the production, misfolding, aggregation, transport and degradation of α-syn that may lead to Parkinson's Disease (PD). Deregulated α-syn degradation is predicted to be crucialfor PD pathogenesis. This model is described in the article: What can trigger the onset of Parkinson's disease - A modeling study based on a compartmental model of α-synuclein transport and aggregation in neurons. Kuznetsov IA, Kuznetsov AV. Math Biosci 2016 Aug; 278: 22-29 Abstract: The aim of this paper is to develop a minimal model describing events leading to the onset of Parkinson's disease (PD). The model accounts for α-synuclein (α-syn) production in the soma, transport toward the synapse, misfolding, and aggregation. The production and aggregation of polymeric α-syn is simulated using a minimalistic 2-step Finke-Watzky model. We utilized the developed model to analyze what changes in a healthy neuron are likely to lead to the onset of α-syn aggregation. We checked the effects of interruption of α-syn transport toward the synapse, entry of misfolded (infectious) α-syn into the somatic and synaptic compartments, increasing the rate of α-syn synthesis in the soma, and failure of α-syn degradation machinery. Our model suggests that failure of α-syn degradation machinery is probably the most likely cause for the onset of α-syn aggregation leading to PD. This model is hosted on BioModels Database and identified by: BIOMD0000000615. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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.

Project description:Sass2009 - Approach to an α-synuclein-based BST model of Parkinson's disease This model is described in the article: 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. 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. This model is hosted on BioModels Database and identified by: BIOMD0000000575. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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.

Project description:This a model from the article: Modelling the Role of UCH-L1 on Protein Aggregation in Age-Related Neurodegeneration. Proctor CJ, Tangeman PJ, Ardley HC. PLoS One. 2010 Oct 6;5(10):e13175 20949132 , Abstract: Overexpression of the de-ubiquitinating enzyme UCH-L1 leads to inclusion formation in response to proteasome impairment. These inclusions contain components of the ubiquitin-proteasome system and α-synuclein confirming that the ubiquitin-proteasome system plays an important role in protein aggregation. The processes involved are very complex and so we have chosen to take a systems biology approach to examine the system whereby we combine mathematical modelling with experiments in an iterative process. The experiments show that cells are very heterogeneous with respect to inclusion formation and so we use stochastic simulation. The model shows that the variability is partly due to stochastic effects but also depends on protein expression levels of UCH-L1 within cells. The model also indicates that the aggregation process can start even before any proteasome inhibition is present, but that proteasome inhibition greatly accelerates aggregation progression. This leads to less efficient protein degradation and hence more aggregation suggesting that there is a vicious cycle. However, proteasome inhibition may not necessarily be the initiating event. Our combined modelling and experimental approach show that stochastic effects play an important role in the aggregation process and could explain the variability in the age of disease onset. Furthermore, our model provides a valuable tool, as it can be easily modified and extended to incorporate new experimental data, test hypotheses and make testable predictions. 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. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not. 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.

Project description:Ouzounoglou2014 - Modeling of alpha-synuclein effects on neuronal homeostasis This model is described in the article: In silico modeling of the effects of alpha-synuclein oligomerization on dopaminergic neuronal homeostasis. Ouzounoglou E, Kalamatianos D, Emmanouilidou E, Xilouri M, Stefanis L, Vekrellis K, Manolakos ES. BMC Syst Biol 2014; 8: 54 Abstract: BACKGROUND: Alpha-synuclein (ASYN) is central in Parkinson's disease (PD) pathogenesis. Converging pieces of evidence suggest that the levels of ASYN expression play a critical role in both familial and sporadic Parkinson's disease. ASYN fibrils are the main component of inclusions called Lewy Bodies (LBs) which are found mainly in the surviving neurons of the substantia nigra. Despite the accumulated knowledge regarding the involvement of ASYN in molecular mechanisms underlying the development of PD, there is much information missing which prevents understanding the causes of the disease and how to stop its progression. RESULTS: Using a Systems Biology approach, we develop a biomolecular reactions model that describes the intracellular ASYN dynamics in relation to overexpression, post-translational modification, oligomerization and degradation of the protein. Especially for the proteolysis of ASYN, the model takes into account the biological knowledge regarding the contribution of Chaperone Mediated Autophagy (CMA), macro-autophagic and proteasome pathways in the protein's degradation. Importantly, inhibitory phenomena, caused by ASYN, concerning CMA (more specifically the lysosomal-associated membrane protein 2a, abbreviated as Lamp2a receptor, which is the rate limiting step of CMA) and the proteasome are carefully modeled. The model is validated by simulation studies of known experimental overexpression data from SH-SY5Y cells and the unknown model parameters are estimated either computationally or by experimental fitting. The calibrated model is then tested under three hypothetical intervention scenarios and in all cases predicts increased cell viability that agrees with experimental evidence. The biomodel has been annotated and is made available in SBML format. CONCLUSIONS: The mathematical model presented here successfully simulates the dynamic phenomena of ASYN overexpression and oligomerization and predicts the biological system's behavior in a number of scenarios not used for model calibration. It allows, for the first time, to qualitatively estimate the protein levels that are capable of deregulating proteolytic homeostasis. In addition, it can help form new hypotheses for intervention that could be tested experimentally. Note: The model contains reactions of species located in different compartments. If the model is applied using volume sizes unequal to one, an extension of the model might be reasonable to guarantee mass conservation. This model is hosted on BioModels Database and identified by: BIOMD0000000559. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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.

Dataset Information

Sneppen2009 - Modeling proteasome dynamics in Parkinson's disease

Publications

Modeling proteasome dynamics in Parkinson's disease.

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