nyman3

The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000423) Biomodels notes: The model reproduces figure 5b,5c and 5d of the reference publication. The y-axis of the plots in the paper are rescaled. To reproduce the plot in the paper, 1) multiply model variable measIRp by a scaling factor of 31.8, 2) multiply model variable measIRS1 by a scaling factor of 21.2 and 3) multiply model variable IRmem by a scaling factor of 10. The model simulation was done using Copasi v4.8 (Build 35). The data were obtained from Copasi and plotted using Gnuplot. JWS Online curation: This model was curated by reproducing the figures as described in the BioModels Notes. No additional changes were made.

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Abstract
Insulin signaling through insulin receptor (IR) and insulin receptor substrate-1 (IRS1) is important for insulin control of target cells. We have previously demonstrated a rapid and simultaneous overshoot behavior in the phosphorylation dynamics of IR and IRS1 in human adipocytes. Herein, we demonstrate that in murine adipocytes a similar overshoot behavior is not simultaneous for IR and IRS1. The peak of IRS1 phosphorylation, which is a direct consequence of the phosphorylation and the activation of IR, occurs earlier than the peak of IR phosphorylation. We used a conclusive modeling framework to unravel the mechanisms behind this counter-intuitive order of phosphorylation. Through a number of rejections, we demonstrate that two fundamentally different mechanisms may create the reversed order of peaks: (i) two pools of phosphorylated IR, where a large pool of internalized IR peaks late, but phosphorylation of IRS1 is governed by a small plasma membrane-localized pool of IR with an early peak, or (ii) inhibition of the IR-catalyzed phosphorylation of IRS1 by negative feedback. Although (i) may explain the reversed order, this two-pool hypothesis alone requires extensive internalization of IR, which is not supported by experimental data. However, with the additional assumption of limiting concentrations of IRS1, (i) can explain all data. Also, (ii) can explain all available data. Our findings illustrate how modeling can potentiate reasoning, to help draw nontrivial conclusions regarding competing mechanisms in signaling networks. Our work also reveals new differences between human and murine insulin signaling.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
default default 3.0 1.0
Id Name Initial quantity Compartment Fixed
IR IR 8.94067597532632 default (default)
IRS IRS 9.43998194225544 default (default)
IRSiP IRSiP 0.560018057744573 default (default)
IRi IRi 0.00000483863890758515 default (default)
IRiP IRiP 0.424076631823384 default (default)
IRins IRins 0.59688996214639 default (default)
IRp IRp 0.0383525925240207 default (default)
X X 9.99635886407151 default (default)
Xp Xp 0.00364113592848386 default (default)

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
v1a v1a IR > IRins

k1a * ins * IR + k1aBasic * IR
v1b v1b IRins > IR

k1b * IRins
v1c v1c IRins > IRp

k1c * IRins
v1d v1d IRp > IRiP

k1d * IRp
v1e v1e IRiP > IRi

IRiP * (k1e + k1f * Xp / (1 + Xp))
v1g v1g IRp > IR

k1g * IRp
v1r v1r IRi > IR

k1r * IRi
v2 v2 IRS > IRSiP

k21 * IRS * (IRp + k22 * IRiP) / (1 + km23 * Xp)
v3 v3 X > Xp

k3 * X * IRSiP
vm2 vm2 IRSiP > IRS

km2 * IRSiP
vm3 vm3 Xp > X

km3 * Xp

Global parameters

Id Value
IRmem 0.0
ins 100.0
k1a 0.153418
k1aBasic 0.0383389
k1b 0.0000034699
k1c 0.574266
k1d 4.78844
k1e 0.0000525027
k1f 119.353
k1g 4.14899
k1r 37954.7
k21 538004.0
k22 0.0000017252
k3 0.0000862917
km2 262759.0
km23 88.9096
km3 0.132671
measIRS1 0.0
measIRp 0.0

Local parameters

Id Value Reaction

Assignment rules

Definition
IRmem = (IRp + IRins + IR) * 10.0
measIRp = (IRp + IRiP) * 31.8
measIRS1 = IRSiP * 21.2

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments