Download pathway_cell_models

Biological pathway and
systems analysis
An introduction
Biomedicine ‘after the human genome’
Patient
Molecular basis of
disease
Current disease
models
Molecular building
blocks
genes
proteins
very data-rich about genes, genome
organisation, proteins, biochemical
function of individual biomolecules
Patient
Physiology
Clinical data
Molecular basis of
disease
Current disease
models
Molecular building
blocks
genes
proteins
Disease
manifestation in
organs, tissues,
cells
?
Molecular
organisation
Patient
physiology, clinical
data
Complex
disease models
Disease
manifestation in
organs, tissues,
cells
tissues
organs
Computational
modelling
Molecular building
blocks
genes
proteins
Molecular
organisation
Global approaches: Systems Biology
Perturbation
Living cell
Dynamic response
Bioinformatics
Mathematical
modelling
cell network
modelling
Simulation
“Virtual cell”
•Basic principles
•Applied uses, e.g.
drug design
Dynamic biochemistry
• Biomolecular interactions
• Protein-ligand interactions
• Metabolism and signal transduction
• Databases and analysis tools
• Metabolic and signalling simulation
• Metabolic databases and simulation
• Dynamic models of cell signalling
Dynamic Pathway Models
• Forefront of the field of systems biology
• Main types
Metabolic networks
Gene networks
Signal transduction networks
• Two types of formalism appearing in the
literature:
– data mining
 e.g. genome expression at gene or protein level
 contribute to conceptualisations of pathways
– simulations of established conceptualisations
Dynamic models of cell
signalling
…from pathway interaction
and molecular data
Erk1/Erk2 Mapk
Signaling pathway
…to dynamic models of pathway
function
Schoeberl
et al., 2002
Simulations: Dynamic Pathway Models
Epidermal growth factor (EGF) pathway
•
These have recently come to the
forefront due to emergence of
high-throughput technologies.
•
Composed of theorised/
validated pathways with kinetic
data attached to every
biochemical reaction
- this enables one to simulate the
change in concentrations of the
components of the pathway over
time given initial parameters.
•
Schoeberl et al (2002) Nat. Biotech 20: 370
These concentrations underlie cell
behaviour.
The epidermal growth factor receptor
(EGFR) pathway
The effect of the number of active EGFR
molecules on ERK activation
EGFR
PLC
PKC
ERK TFs
Ras
MAPK
500,000 active
receptors
PI3K
PKB/Akt
Functional targets
CELL GROWTH AND PROLIFERATION
50,000 active
receptors =
Inhibition by one order
of magnitude
Schoeberl et al., 2002, Nat. Biotech. 20: 370
The effect of active EGFR number on ERK
activation
500,000 active
receptors
50,000 active
receptors
Can this be achieved
by receptor
inactivation alone?
The effect of active EGFR number on ERK
activation
50,000 active
receptors
with normal levels of
ERK
or
ERK overexpression
and cross-activation
Hunter and Borg (2003)
Virtual Physiological Human
Simulation of complex models of cells, tissues and organs
www.vph-noe.eu
•Heart modelling: 40+ years of mathematical modeling of
electrophysiology and tissue mechanics
•New models integrate molecular mechanisms and large-scale gene
expression profiles
Multi-level modelling
patient
integration across scales through
computational modelling
organ
Anatomy and integrative
function, electrical dynamics
Vessels, circulatory flow,
exchanges, energy metabolism
cell
Cell models, ion fluxes,
action potential, molecules,
functional genomics
Spatial distribution of key proteins
• Transmural expression differences of an ion channel protein leads to
different action potential profiles at the epicardium, midwall and
endocardium
• Arrhythmias
Hunter et al (2005) Mechanisms of Ageing and Development
126:187–192.
Virtual Physiological Human Project
www.vph-noe.eu/
The Virtual Physiological Human
https://www.youtube.com/watch?v=CM76-mS84Xs
The hallmarks of systems biology
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formulate a general or specific question
define the components of a biological system
collect previous relevant datasets
integrate them to formulate an initial model of the system
generate testable predictions and hypotheses
systematically perturb the components of the system
experimentally or through simulation
study the results
compare the responses observed to those predicted by the
model
refine the model so that its predictions fit best to the
experimental observations
conceive and test new experimental perturbations to
distinguish between the multiple competing hypotheses
iterate the process until a suitable response to the initial
question is obtained