Transcript Lecture 9: Biological Pathway Simulation

LSM3241: Bioinformatics and Biocomputing
Lecture 9: Biological Pathway Simulation
Prof. Chen Yu Zong
Tel: 6874-6877
Email: [email protected]
http://xin.cz3.nus.edu.sg
Room 07-24, level 7, SOC1, NUS
Biomolecular Interaction: Enzyme + Substrate
E + S ==> E + P
• This is a generalization of how a biochemist might
represent the function of enzymes.
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Biomolecular Interaction: Enzyme + Substrate
E + S ==> E + P
kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme
K
P
ATP
ADP
• Here is an example of the generalization represented by
two different ways.
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Biomolecular Interaction: Enzyme + Substrate
inactive
enzyme
Active
enzyme
Kinase-ATP
complex
ADP
• This is another representation.
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Spoke and Matrix Models of Protein-Protein Interactions
Vrp1 (bait), Las17, Rad51, Sla1, Tfp1, Ypt7
Spoke
Possible Actual
Topology
Simple model
Intuitive, more accurate, but can
misrepresent
Matrix
Theoretical max.
no. of interactions,
but many FPs
Bader&Hogue Nature Biotech. 2002 Oct 20(10):991-7
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Cell Polarity
Cell Wall Maintenance
Cell Structure
Mitosis
Chromosome Structure
DNA Synthesis
DNA Repair
Unknown
Others
Synthetic Genetic Interactions in Yeast
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Tong, Boone
Metabolic Pathway: ATP Production
• Glycolysis
– Phosphorylation
– Pyruvate
• Anaerobic respiration
• Lactate production
• 2 ATPs produced
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Cyclic Metabolic Pathway
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Methods of Metabolic Engineering
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Generic Signaling Pathway
Signal
Receptor
(sensor)
Transduction
Cascade
Targets
Metabolic
Enzyme
Response
Altered
Metabolism
Gene Regulator
Altered
Gene
Expression
Cytoskeletal Protein
Altered Cell
Shape or
Motility
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Components of Signaling
What can be the Signal?
External message to the cell
•
•
•
•
•
•
•
•
Peptides / Proteins- Growth Factors
Amino acid derivatives - epinephrine, histamine
Other small biomolecules - ATP
Steroids, prostaglandins
Gases - Nitric Oxide (NO)
Photons
Damaged DNA
Odorants, tastants
Signal = LIGAND
Ligand- A molecule that binds to a specific site on
another molecule, usually a protein, ie receptor
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Components of Signaling
What are Receptors?
Sensors, what the signal/ligand binds to initiate ST
Cell surface
Cell-Surface
Receptor
Hydrophillic Ligand
Plasma membrane
Intracellular
Hydrophobic
Ligand
Carrier Protein
Intracellular
Receptor
Nucleus
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Generic Signal Transduction
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RTK Signal Transduction
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Signal Transduction
Downstream effectors
Protein Signaling Modules (Domains)
SH2 and PTB bind to tyrosine phosphorylated sites
SH3 and WW bind to proline-rich sequences
PDZ domains bind to hydrophobic residues at the C-termini of target proteins
PH domains bind to different phosphoinositides
FYVE domains specifically bind to Pdtlns(3)P (phosphatidylinositol 3-phosphate)
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Mechanisms for Activation of Signaling Proteins by RTKs
Activation by membrane translocation
Activation by a conformational change
Activation by tyrosine phosphorylation
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Mechanisms for Attenuation & Termination of RTK Activation
1) Ligand antagonists
2) Receptor antagonists
3) Phosphorylation and dephosphorylation
4) Receptor endocytosis
5) Receptor degradation by the ubiquitin-proteosome pathway
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Activation of MAPK Pathways by Multiple Signals
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Growth, differentiation, inflammation, apoptosis -> tumorigenesis
Overview of
MAPK Signaling
Pathways
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The MAPK Pathway Activated by RTK
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P
RTK
ST- PI3K
pathway
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Apoptosis
Pathways
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TGF
Pathway
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Constructing a pathway model:
things to consider
1. Dynamic nature of
biological networks.
Biological pathway is
more than a topological
linkage of molecular
networks.
Pathway models can be
based on network
characteristics including
those of invariant
features.
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Constructing a pathway model:
things to consider
2. Abstraction Resolution:
• How much do we get into details?
• What building blocks do we use to
describe the network?
High
resolution
(A) Substrates and proteins
(B) Pathways
(C) “special pathways”
Low
resolution
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Constructing a pathway model
Step I - Definitions
We begin with a very simple imaginary metabolic network represented
as a directed graph:
Vertex – protein/substrate
concentration.
Edge - flux (conversion mediated by
proteins of one substrate into the
other)
How do we
define a
biologically
significant
system
boundary?
Internal flux edge
External flux edge
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Constructing a pathway model
Step II: Interaction Kinetics
E + S ==> E + P
kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme
K
P
ATP
ADP
Reversibility of Chemical Reactions:
Equilibrium
H2  2H
• Chemical reactions are reversible
• Under certain conditions (concentration, temperature)
both reactants and products exist together in
equilibrium state
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Reaction Rates
Net reaction rate = forward rate – reverse rate
• In equilibrium: Net reaction rate = 0
• When reactants “just” brought together: Far from
equilibrium, focus only on forward rate
• But, same arguments apply to the reverse rate
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The Differential Rate Law
• How does the rate of the reaction depend on
concentration? E.g.
3A + 2B  C + D
rate = k [A]m[B]n
(Specific
reaction)
rate
constant
Order of
reaction
with
respect
to A
m+n:
Overall
order of
the
reaction
Order of
reaction
with
respect
to B
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Rate Constants and Reaction Orders
• Each reaction is characterized by its own rate
constant, depending on the nature of the
reactants and the temperature
• In general, the order with respect to each
reagent must be found experimentally (not
necessarily equal to stoichiometric coefficient)
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Elementary Processes and Rate Laws
• Reaction mechanism: The collection of elementary
processes by which an overall reaction occurs
• The order of an elementary process is predictable
Unimolecular
A*  B
K+ [A]
First
order
Bimolecular
A +BC+D
K+ [A] [B]
Second
order
Trimolecular
A + B + C  D + E K+ [A] [B] [C]
Third
order
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Elementary Processes and Rate Laws
• Reaction mechanism: The collection of elementary
processes by which an overall reaction occurs
• The order of an elementary process is predictable
Unimolecular
A*  B
K+ [A] – K- [B]
First
order
Bimolecular
A + B  C + D
K+ [A] [B] – K- [C] [D]
Second
order
Trimolecular
Third
A + B + C  D + E K+ [A] [B] [C] – K- [D] [E] order
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Constructing a pathway model
Step III - Dynamic mass balance
Concentration
vector
Stoichiometry Flux vector
Matrix
dx
 S v
dt
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A ‘simple’ ODE model of yeast glycolysis
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A model pathway system
and its time-dependent behavior
Positive Feedback Loop
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A model pathway system
and its time-dependent behavior
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A model pathway system
and its time-dependent behavior
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