nyman2

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Mathematical modeling improves EC50 estimations from classical dose-response curves.

  • Elin Nyman
  • Isa Lindgren
  • William Lövfors
  • Karin Lundengård
  • Ida Cervin
  • Theresia Arbring Sjöström
  • Jordi Altimiras
  • Gunnar Cedersund
FEBS J. 2015; 282 (5): 951-962
Abstract
UNLABELLED: The β-adrenergic response is impaired in failing hearts. When studying β-adrenergic function in vitro, the half-maximal effective concentration (EC50 ) is an important measure of ligand response. We previously measured the in vitro contraction force response of chicken heart tissue to increasing concentrations of adrenaline, and observed a decreasing response at high concentrations. The classical interpretation of such data is to assume a maximal response before the decrease, and to fit a sigmoid curve to the remaining data to determine EC50 . Instead, we have applied a mathematical modeling approach to interpret the full dose-response curve in a new way. The developed model predicts a non-steady-state caused by a short resting time between increased concentrations of agonist, which affect the dose-response characterization. Therefore, an improved estimate of EC50 may be calculated using steady-state simulations of the model. The model-based estimation of EC50 is further refined using additional time-resolved data to decrease the uncertainty of the prediction. The resulting model-based EC50 (180-525 nm) is higher than the classically interpreted EC50 (46-191 nm). Mathematical modeling thus makes it possible to re-interpret previously obtained datasets, and to make accurate estimates of EC50 even when steady-state measurements are not experimentally feasible.
DATABASE: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database, and may be accessed at http://jjj.bio.vu.nl/database/nyman.

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 0.0 1.0
Id Name Initial quantity Compartment Fixed
bact 6.36298895958195 default
beta 47.5628313437178 default
betaphos 46.0741796964978 default
cAMP 0.119663775088957 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
v_1 beta = bact

kbasal * beta
v_2 beta = bact

kH * kratio * h * beta
v_3 betaphos = beta

k1 * betaphos
v_4 bact = betaphos

bact * k2
v_5 ∅ = cAMP

bact * k3
v_6 ∅ = cAMP

cAMP0
v_7 cAMP = ∅

k4 * cAMP

Global parameters

Id Value
FoC nan
cAMP0 18.307
h 0.0
k1 0.11566
k2 0.83749
k3 1.2313
k4 218.46
kH 0.00077465
kbasal 0.11204
kratio 5.5528
scale 8.36

Local parameters

Id Value Reaction

Assignment rules

Definition
FoC = scale * cAMP

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments
gt(time, 50 / 60) h = 0.01
gt(time, 200 / 60) h = 0.1
gt(time, 350 / 60) h = 1
gt(time, 500 / 60) h = 10
gt(time, 650 / 60) h = 100
gt(time, 800 / 60) h = 300
gt(time, 950 / 60) h = 1000
gt(time, 1100 / 60) h = 3000
gt(time, 1250 / 60) h = 10000