Internal metabolite concentraitons for mutants, perturbation and time series samples including mutant enzyme fold change

Contains relative mutant (OE, KO) perturbation and time series samples metabolite concentrations and enzyme fold change of targeted enzymes used for model validation. Measured are the relative fold change, Mean and SD of log2 fold change values are based on multiple measurements per sample (minimum of three). Contains input data for Automated Model simulations pipeline to load and update the models metabolite concentrations and enzyme parameters to simulate all sample using a custom python script ...

Creator: Niels Zondervan

Submitter: Niels Zondervan

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Dynamic model of glycolysis, pyruvate metabolism and NoxE in M. pneumonaie with innitial parameter values and annotation

Dynamic model of glycolysis, pyruvate metabolism and NoxE. The model is parameterized by selecting the best out of 100 parameter set using Copasi's Genetic algorithm with 1000 itterations and 500 simmulatanious models.

Creator: Niels Zondervan

Submitter: Niels Zondervan

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Design principles of ROS dynamic networks relevant to precision therapies for age-related diseases

Abstract (Expand)

The eminently complex regulatory network protecting the cell against oxidative stress, surfaces in several disease maps, including that of Parkinson’s disease (PD). How this molecular networking achieves … its various functionalities and how processes operating at the seconds-minutes time scale cause a disease at a time scale of multiple decennia is enigmatic. By computational analysis, we here disentangle the reactive oxygen species (ROS) regulatory network into a hierarchy of subnetworks that each correspond to a different functionality. The detailed dynamic model of ROS management obtained integrates these functionalities and fits in vitro data sets from two different laboratories. The model shows effective ROS-management for a century, followed by a sudden system’s collapse due to the loss of p62 protein. PD related conditions such as lack of DJ-1 protein or increased α-synuclein accelerated the system’s collapse. Various in-silico interventions (e.g. addition of antioxidants or caffeine) slowed down the collapse of the system in silico, suggesting the model may help discover new medicinal and nutritional therapies.

Authors: Alexey Kolodkin, Raju Prasad Sharma, Anna Maria Colangelo, Andrew Ignatenko, Francesca Martorana, Danyel Jennen, Jacco J. Briede, Nathan Brady, Matteo Barberis, Thierry D.G.A. Mondeel, Michele Papa, Vikas Kumar, Bernhard Peters, Alexander Skupin, Lilia Alberghina, Rudi Balling, Hans V. Westerhoff

Date Published: No date defined

Publication Type: Not specified

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