Indicate species boundary condition
BoundaryCondition property indicates whether reactions affect a species
BoundaryCondition of a species is
(default), the reactions can modify the species quantity. If a species is modified by
reactions, then rules (repeated assignment rule, rate rule, or algebraic rule) cannot
modify its value. SimBiology considers a reaction to modify a species when the net
stoichiometry for the species is non-zero. For example, the reaction
X -> 2*X modifies
X, but the reaction
E -> Y + E does
not modify E.
BoundaryCondition of a species is
then the value of the species is not changed by reactions during model simulation, even if
the net stoichiometry is non-zero. Set the
BoundaryCondition of a
true if you want the species to participate in the reaction
but you want to determine the value of that species using a rule instead. For example, set
BoundaryCondition of species X to
true to specify its value using a repeated assignment rule but also
to use species X in a reaction with
kinetics, for example,
X + Y ->
For details on how these two properties affect a species quantity during simulation, see How Species Amounts Change During Simulations.
Consider the following two use cases of boundary conditions:
Modeling receptor-ligand interactions that affect the rate of change of the receptor but not the ligand. For example, in response to hormone, steroid receptors such as the glucocorticoid receptor (GR) translocate from the cytoplasm (
cyt) to the nucleus (
nuc). The hsp90/ hsp70 chaperone complex directs this nuclear translocation [Pratt 2004]. The natural ligand for GR is cortisol; the synthetic hormone dexamethasone (
dex) is used in place of cortisol in experimental systems. In this system dexamethasone participates in the reaction but the quantity of dexamethasone in the cell is regulated using a rule. To simply model translocation of GR you could use the following reactions:
Formation of the chaperone-receptor complex,
Hsp90_complex + GR_cyt -> Hsp90_complex:GR_cyt
In response to the synthetic hormone dexamethasone (
dex), GR moves from the cytoplasm to the nucleus.For
Hsp90_complex:GR_cyt + dex -> Hsp90_complex + GR_nuc + dex
dex,In this example
BoundaryCondition = true; ConstantAmount = false
dexis modeled as a boundary condition with a rule to regulate the rate of change of
dexin the system. Here, the quantity of
dexis not determined by the rate of the second reaction but by a rate rule such aswhich is specified in the SimBiology® software as
ddex/dt = 0.001
dex = 0.001
Modeling the role of nucleotides (for example, GTP, ATP, cAMP) and cofactors (for example, Ca++, NAD+, coenzyme A). Consider the role of GTP in the activation of Ras by receptor tyrosine kinases.
Ras-GDP + GTP -> Ras-GTP + GDP
For GTP, BoundaryCondition = true; ConstantAmount = true
Model GTP and GDP with boundary conditions, thus making them boundary species. In addition, you can set the
ConstantAmountproperty of these species to
trueto indicate that their quantity does not vary during a simulation.
|Applies to||Object: species|
Simulate a Model with a Boundary Condition for a Species
This example illustrates how to use the
of a species so that the species amount is not modified by the reaction
it participates in, but by a user-defined dose object.
Load a sample project.
A SimBiology model named
m1 is loaded to
the MATLAB Workspace. The model is a simple radioactive decay model
in which two species (
are modified by the following reaction.
SimBiology Reaction Array Index: Reaction: 1 x -> z
Simulate the model and view results before adding any boundary conditions.
[t,x,names] = sbiosimulate(m1); plot(t,x); legend(names) xlabel('Time'); ylabel('Amount');
RepeatDose object to the model
and specify the species to be dosed, dose amount, dose schedule, and
d1 = adddose(m1,'d1','repeat'); set(d1,'TargetName','z','Amount',100.0,'Interval',1.0,'RepeatCount',8); set(d1,'TimeUnits','second','AmountUnits','molecule');
BoundaryCondition of species
be true so that the species will be modified by the dose object
but not by the reaction.
Simulate the model by applying the dose object.
[t2,x2,names] = sbiosimulate(m1,d1);
Plot the results. Notice that the amount of species
now modified by the repeated dose object, but not by the reaction.
[t2,x2,names] = sbiosimulate(m1,d1); plot(t2,x2); legend(names); xlabel('Time'); ylabel('Amount');
Pratt, W.B., Galigniana, M.D., Morishima, Y., Murphy, P.J. (2004), Role of molecular chaperones in steroid receptor action, Essays Biochem, 40:41-58.