Lee2008 - ERK and PI3K signal integration by Myc
Model Identifier
BIOMD0000000818
Short description
Mechanisitc model of PI3K and ERK signal integration by Myc. ERK and PI3K regulated Myc satbility by phosphorylating the same. (PMID:18463697)
Format
SBML
(L2V4)
Related Publication
-
Sensing and integration of Erk and PI3K signals by Myc.
- Lee T, Yao G, Nevins J, You L
- PLoS computational biology , 2/ 2008 , Volume 4 , Issue 2 , pages: e1000013 , PubMed ID: 18463697
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
- The transcription factor Myc plays a central role in regulating cell-fate decisions, including proliferation, growth, and apoptosis. To maintain a normal cell physiology, it is critical that the control of Myc dynamics is precisely orchestrated. Recent studies suggest that such control of Myc can be achieved at the post-translational level via protein stability modulation. Myc is regulated by two Ras effector pathways: the extracellular signal-regulated kinase (Erk) and phosphatidylinositol 3-kinase (PI3K) pathways. To gain quantitative insight into Myc dynamics, we have developed a mathematical model to analyze post-translational regulation of Myc via sequential phosphorylation by Erk and PI3K. Our results suggest that Myc integrates Erk and PI3K signals to result in various cellular responses by differential stability control of Myc protein isoforms. Such signal integration confers a flexible dynamic range for the system output, governed by stability change. In addition, signal integration may require saturation of the input signals, leading to sensitive signal integration to the temporal features of the input signals, insensitive response to their amplitudes, and resistance to input fluctuations. We further propose that these characteristics of the protein stability control module in Myc may be commonly utilized in various cell types and classes of proteins.
Contributors
Submitter of the first revision: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari
Metadata information
is (2 statements)
isDescribedBy (1 statement)
hasTaxon (1 statement)
hasProperty (3 statements)
occursIn (1 statement)
isDescribedBy (1 statement)
hasTaxon (1 statement)
hasProperty (3 statements)
Mathematical Modelling Ontology
Ordinary differential equation model
Pathway Ontology growth factor signaling pathway
Gene Ontology regulation of protein stability
Pathway Ontology growth factor signaling pathway
Gene Ontology regulation of protein stability
occursIn (1 statement)
Curation status
Curated
Modelling approach(es)
Tags
Connected external resources
SBGN view in Newt Editor
| Name | Description | Size | Actions |
|---|---|---|---|
Model files |
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| Lee2008.xml | SBML L2V4 file for Lee2008 model | 63.59 KB | Preview | Download |
Additional files |
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| Lee2008.cps | COPASI 4.24 (build 217) file for Lee2008 model | 96.75 KB | Preview | Download |
| Lee2008.sedml | SEDML file for Lee2008 model | 4.49 KB | Preview | Download |
- Model originally submitted by : Krishna Kumar Tiwari
- Submitted: Sep 19, 2019 2:17:35 PM
- Last Modified: Sep 19, 2019 2:17:35 PM
Revisions
-
Version: 3
- Submitted on: Sep 19, 2019 2:17:35 PM
- Submitted by: Krishna Kumar Tiwari
- With comment: Automatically added model identifier BIOMD0000000818
Legends
: Variable used inside SBML models
: Variable used inside SBML models
Species
| Species | Initial Concentration/Amount |
|---|---|
| AKTp RAC-alpha serine/threonine-protein kinase |
0.0 nmol |
| GSK3Bp Glycogen synthase kinase-3 beta |
0.0 nmol |
| Myc thr58 Myc proto-oncogene protein |
0.0 nmol |
| AKT RAC-alpha serine/threonine-protein kinase |
0.6 nmol |
| Myc ser62 Myc proto-oncogene protein |
0.0 nmol |
| Myc Myc proto-oncogene protein |
0.0 nmol |
| GSK3B Glycogen synthase kinase-3 beta |
0.6 nmol |
Reactions
| Reactions | Rate | Parameters |
|---|---|---|
| AKT => AKTp; PI3K | Cell*k_ap*PI3K*AKT/(K_AP+AKT) | K_AP = 0.01 nmol/l; k_ap = 360.0 1/h |
| AKTp => AKT | Cell*k_AD*AKTp/(K_AD+AKTp) | k_AD = 72.0 nmol/(h*l); K_AD = 0.01 nmol/l |
| GSK3B => GSK3Bp; AKTp | Cell*k_GP*AKTp*GSK3B/(K_GP+GSK3B) | K_GP = 0.01 nmol/l; k_GP = 360.0 1/h |
| Myc_ser62 => Myc_thr58; GSK3B | Cell*k_MT*GSK3B*Myc_ser62/(K_MT+Myc_ser62) | k_MT = 0.4 1/h; K_MT = 0.01 nmol/l |
| Myc_thr58 => | Cell*dMT*Myc_thr58 | dMT = 2.08 1/h |
| Myc => | Cell*dM*Myc | dM = 2.08 1/h |
| => Myc; GF | Cell*kM*GF | kM = 1.0 1/h |
Curator's comment:
(added: 19 Sep 2019, 14:16:40, updated: 19 Sep 2019, 14:16:40)
(added: 19 Sep 2019, 14:16:40, updated: 19 Sep 2019, 14:16:40)
Figure 1B from the literature is reproduced. Model encoded and simulated using COPASI 4.24 (built217). In the model, units are taken in nM instead of uM (as given in literature) due to COPASI bug with not handling umol unit well and it gives error in SBML check.