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BIOMD0000000556 - Ortega2013 - Interplay between secretases determines biphasic amyloid-beta level

 

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Reference Publication
Publication ID: 23152503
Ortega F, Stott J, Visser SA, Bendtsen C.
Interplay between α-, β-, and γ-secretases determines biphasic amyloid-β protein level in the presence of a γ-secretase inhibitor.
J. Biol. Chem. 2013 Jan; 288(2): 785-792
Computational Biology, Discovery Sciences, AstraZeneca, Alderley Park, Macclesfield SK10 4TG, United Kingdom.  [more]
Model
Original Model: BIOMD0000000556.origin
Submitter: Audald Lloret i Villas
Submission ID: MODEL1409240000
Submission Date: 24 Sep 2014 10:25:01 UTC
Last Modification Date: 08 Apr 2016 18:43:10 UTC
Creation Date: 23 Oct 2014 12:29:00 UTC
Encoders:  Audald Lloret i Villas
   Jonathan Stott
set #1
bqbiol:isVersionOf Gene Ontology amyloid precursor protein catabolic process
Gene Ontology beta-amyloid formation
set #2
bqbiol:hasProperty Human Disease Ontology Alzheimer's disease
set #3
bqbiol:hasTaxon Taxonomy Homo sapiens
Notes
Ortega2013 - Interplay between secretases determines biphasic amyloid-beta level

This model is described in the article:

Ortega F, Stott J, Visser SA, Bendtsen C.
J. Biol. Chem. 2013 Jan; 288(2): 785-792

Abstract:

Amyloid-? (A?) is produced by the consecutive cleavage of amyloid precursor protein (APP) first by ?-secretase, generating C99, and then by ?-secretase. APP is also cleaved by ?-secretase. It is hypothesized that reducing the production of A? in the brain may slow the progression of Alzheimer disease. Therefore, different ?-secretase inhibitors have been developed to reduce A? production. Paradoxically, it has been shown that low to moderate inhibitor concentrations cause a rise in A? production in different cell lines, in different animal models, and also in humans. A mechanistic understanding of the A? rise remains elusive. Here, a minimal mathematical model has been developed that quantitatively describes the A? dynamics in cell lines that exhibit the rise as well as in cell lines that do not. The model includes steps of APP processing through both the so-called amyloidogenic pathway and the so-called non-amyloidogenic pathway. It is shown that the cross-talk between these two pathways accounts for the increase in A? production in response to inhibitor, i.e. an increase in C99 will inhibit the non-amyloidogenic pathway, redirecting APP to be cleaved by ?-secretase, leading to an additional increase in C99 that overcomes the loss in ?-secretase activity. With a minor extension, the model also describes plasma A? profiles observed in humans upon dosing with a ?-secretase inhibitor. In conclusion, this mechanistic model rationalizes a series of experimental results that spans from in vitro to in vivo and to humans. This has important implications for the development of drugs targeting A? production in Alzheimer disease.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Model
Publication ID: 23152503 Submission Date: 24 Sep 2014 10:25:01 UTC Last Modification Date: 08 Apr 2016 18:43:10 UTC Creation Date: 23 Oct 2014 12:29:00 UTC
Mathematical expressions
Reactions
r0 r1 r2 r3 (ND)
r4 (ND) r5 r3 (D) r4 (D)
Rules
Assignment Rule (variable: den) Rate Rule (variable: APP) Rate Rule (variable: C83) Rate Rule (variable: C99)
Rate Rule (variable: AB) Rate Rule (variable: p3)    
Physical entities
Compartments Species
Brain APP C83 C99
AB X p3
Global parameters
v0 km1 vm1 km3
vm3 km4 vm4 km5
vm5 km2 vm2 kic
kiu1 kiu2 den  
Reactions (8)
 
 r0  → [APP];  
 
 r1 [APP] → [C83];   {C99} , {APP} , {C99}
 
 r2 [APP] → [C99];   {APP}
 
 r3 (ND) [C83] → [p3];   {C99} , {C83} , {C99}
 
 r4 (ND) [C99] → [AB];   {C83} , {C99} , {C83}
 
 r5 [C99] → [C83];   {APP} , {C99} , {APP}
 
 r3 (D) [C83] → [p3];   {X} , {X} , {C83}
 
 r4 (D) [C99] → [AB];   {X} , {X} , {C99}
 
Rules (6)
 
 Assignment Rule (name: den) den = 1+C83/km3*(1+X/kiu1)/(1+X/kic)+C99/km4*(1+X/kiu2)/(1+X/kic)
 
 Rate Rule (name: APP) d [ APP] / d t= (r0-r1)-r2
 
 Rate Rule (name: C83) d [ C83] / d t= (r1+r5)-r3__D
 
 Rate Rule (name: C99) d [ C99] / d t= (r2-r5)-r4__D
 
 Rate Rule (name: AB) d [ AB] / d t= r4__D
 
 Rate Rule (name: p3) d [ p3] / d t= r3__D
 
Functions (4)
 
 Constant flux (irreversible) lambda(v, v)
 
 VD lambda(Vm, X, Kx, S, Km, Den, Vm/(1+X/Kx)*S/Km/Den)
 
 V1,3,4,5 lambda(Vm, S, Km1, M, Km2, Vm*S/Km1/(1+S/Km1+M/Km2))
 
 V2 lambda(Vm, S, Km, Vm*S/Km/(1+S/Km))
 
 Brain Spatial dimensions: 3.0  Compartment size: 1.0
 
 APP
Compartment: Brain
Initial concentration: 0.0
 
 C83
Compartment: Brain
Initial concentration: 0.0
 
 C99
Compartment: Brain
Initial concentration: 0.0
 
 AB
Compartment: Brain
Initial concentration: 0.0
 
 X
Compartment: Brain
Initial concentration: 0.0
Constant
 
 p3
Compartment: Brain
Initial concentration: 0.0
 
Global Parameters (15)
 
 v0
Value: 1.0
Constant
 
 km1
Value: 0.186
Constant
 
 vm1
Value: 1.1
Constant
 
 km3
Value: 28.8
Constant
 
 vm3
Value: 14.6
Constant
 
 km4
Value: 0.915
Constant
 
 vm4
Value: 1.71
Constant
 
 km5
Value: 0.0672
Constant
 
 vm5
Value: 0.0223
Constant
 
 km2
Value: 1.64
Constant
 
 vm2
Value: 0.153
Constant
 
 kic
Value: 0.173
Constant
 
 kiu1
Value: 145.0
Constant
 
 kiu2
Value: 7.31
Constant
 
  den
Value: 1.0
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000556

Curator's comment: (updated: 19 Nov 2014 16:03:20 GMT)

Quantitative modelling of the A? response across a range of inhibitor concentrations in two cell types (see below) from Figure 3 has been reproduced here. Percent of A? concentration after 16 hours along a range of inhibitor concentration (log scale -2 to 4) respect A? concentration when no drug treatment is applied.

Legend:
APPwt = cell type within wild type APP
APPswe = cell type within Swedish mutation APP
DAPT = gamma-secretase inhibitor drug N-[N-(3,5-Difluorophenacetyl)-alanyl]-S-phenylglycine t-butyl ester

Reactions for different conditions are found in Table 1 and 2 of the paper.
Secretase and inhibitor parameter values are found in Table S1a and S1b of the Supplementary section.

The simulation was done using Copasi v4.12 (Build 81) and the plots were generated using Gnuplot. Figure 3 is simulated by dividing the drug condition output by the no-drug condition output. The models with simulation settings can be downloaded from the below links:
- Copasi file of “Ortega2013 - Drug condition”
- Copasi file of “Ortega2013 – No-drug condition”

Additional file(s)
  • Ortega2013 - Interplay between secretases determines biphasic amyloid-beta level:
    Drug condition
  • Ortega2013 - Interplay between secretases determines biphasic amyloid-beta level:
    No-drug condition
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