Transcript Folie 1

Modeling and Simulation
of
Signal Transduction Pathways
Mark Moeller & Björn Oleson
Supervisors:
Klaus Prank
Ralf Hofestädt
Content
• Signal Transduction
• Modeling and Simulation
• Project
Signal Transduction is …
Biochemical Information Network
Transportation
Amplification
of Information
Distribution
from Cell to Cell
and
within Cells
Signal transduction pathways
• receptor protein (cell surface)
transduces
• extracellular signal
into
• intracellular signal
initiating
–signaling cascade
• relaying
• amplifying
• distributing
RELAY
AMPLIFICATION
DIVERGENCE TO
MULTIPLE TARGETS
REGULATION
CHANGES INOF
CYTOSKELETON
METHABOLIC
GENE
EXPRESSION
PATHWAY
Phosphoinositol Pathway
as an Example
Phosphoinositol Pathway
Ligand
Cell Membrane
Receptor

 
PLC
GDP
P
P
PIP2
P
G-Protein
GTP
P KC
Endoplasmic Reticulum
Ca2+-Channel-Protein
Ca2+
Phosphoinositol Pathway

 
PLC
GDP
P
P
P
GTP
P KC
Phosphoinositol Pathway

 
GTP
PLC
P
P
P
P KC
Phosphoinositol Pathway



PLC
GTP
G
DP
P
P
DAG
P
IP3
P KC
Phosphoinositol Pathway

 
PLC
GDP
P KC
P
P
P
Phosphoinositol Pathway

 
PLC
P KC
GDP
P
P
P
Complex ?
Phosphoinositol Pathway
Apoptosis and Growth Network
Ca2+
IP3
PIP2 PLC
PI3-K
Sphingomyeline
PC
PA
DAG
PLD
PKC-
Sphingomyelinase
Ceramide
CAPP
PIP3
PIP2
PI3-K
PIP3
PKC-
Proteinkinase
PKC-
PKC-
Caspase
PKC-
Bcl-2
Apoptosis
Growth
NF-B
Pathway Modeling
Pathway Cartoons Translated into Differential Equations
Parameters Estimated from Measured Data
This allows for:
• a Quantitative Descrition of Pathways
• Testing the Model
• Gaining Insight into the Biochemical Principles
• Observing Experimentally Unobservable Components
• Prediction of new Experiments (in silico Biology)
• Identification of Possible Drug Targets
Deterministic Model vs. Monte Carlo Modeling
Deterministic Approach
• Differential Equations
– Reaction Rates
– Concentrations
• Continuous
Macroscopic
Stochastic Approach
• Monte Carlo Simulation
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Reaction Probabilities
Molecule Numbers
Subcellular Structures
Limited Diffusion
Cellular Geometry
• Discrete
Microscopic
Existing approaches
• Simulators
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–
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MCell
StochSim
Copasi
Gepasi
Virtual Cell
E-Cell
GENESIS
NEURON
• Companies
– Physiome Sciences
– Entelos
– Cellomics
• Databases
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TRANSPATH
TRANSFAC
BIND
DIP
What I am going to do …
molecule
database
Project
biochemical
model
image
data
mathematical
model
other
Monte Carlo simulator
output
visualization
pathway
database
database
So, my work includes …
1. Establish Simulator
2. Run Phosphoinositol Pathway
3. Visualize Output
4. Develop Scripting Language
5. Specify Interfaces to Automatization
6. Specify Relational Database
Thank you !
Useful in silico Prediction of Signaling
Pathways and Networks
• Knowledge of all Players
• Kinetic Properties, Interaction Partners
• Mechanisms of Positive and Negative Regulation
• Subcellular Localizations and Concentrations
• Incorporation of Kinetic and Particularly Spatial Aspects of
Signaling into Models