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Mathematical modeling of the molecular switch of TNFR1-mediated signaling pathways applying Petri net formalism and in silico knockout analysis. | LitMetric

AI Article Synopsis

  • The paper presents a mathematical model using Petri nets to analyze how cell survival, apoptosis, and necroptosis are regulated by tumor necrosis factor 1 (TNFR1) signaling pathways.
  • The model includes 118 biochemical entities and identifies 279 signal pathways, detailing how 120 pathways promote survival while 58 and 35 lead to apoptosis and necroptosis, respectively.
  • The research emphasizes the importance of checkpoints like ubiquitination and NF-κB in regulating these pathways and utilizes a semi-quantitative approach due to limited kinetic data quality.

Article Abstract

The paper describes a mathematical model of the molecular switches of cell survival, apoptosis, and necroptosis in cellular signaling pathways initiated by tumor necrosis factor 1. Based on experimental findings in the literature, we constructed a Petri net model based on detailed molecular reactions of the molecular players, protein complexes, post-translational modifications, and cross talk. The model comprises 118 biochemical entities, 130 reactions, and 299 edges. We verified the model by evaluating invariant properties of the system at steady state and by in silico knockout analysis. Applying Petri net analysis techniques, we found 279 pathways, which describe signal flows from receptor activation to cellular response, representing the combinatorial diversity of functional pathways.120 pathways steered the cell to survival, whereas 58 and 35 pathways led to apoptosis and necroptosis, respectively. For 65 pathways, the triggered response was not deterministic and led to multiple possible outcomes. We investigated the in silico knockout behavior and identified important checkpoints of the TNFR1 signaling pathway in terms of ubiquitination within complex I and the gene expression dependent on NF-κB, which controls the caspase activity in complex II and apoptosis induction. Despite not knowing enough kinetic data of sufficient quality, we estimated system's dynamics using a discrete, semi-quantitative Petri net model.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9467317PMC
http://dx.doi.org/10.1371/journal.pcbi.1010383DOI Listing

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