Why to develop a model by using NTCC calculus?

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Transcript Why to develop a model by using NTCC calculus?

Diana Hermith, BSc. Molecular Biology
[email protected]
Graduate Student
Program in Engineering Emphasis in Computer Systems
(Graduate Research Draft Proposal)
Research in Avispa: Concurrency Theory and Applications
Pontificia Universidad Javeriana, Cali
Cali (Colombia), Tuesday January 13th
2009
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Agenda
I. Introduction
II. State of the Art (Short)
III. Detailed Description of the G Protein Signal
Cascade
IV. Why to develop a model by using NTCC
calculus?
References
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
American Chemical Society, Jun Xu, Ph. D., January 24, 2008, San Diego
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
American Chemical Society, Jun Xu, Ph. D., January 24, 2008, San Diego
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
These interactions can be physical or logical
http://www.scribd.com/doc/48863/CELL-SIGNALING?autodown=pdf
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
Understanding how pathways function is crucial,
since malfunction results in a large number of
diseases such as cancer, diabetes, and
cardiovascular disease.
Furthermore, good predictive models can guide
experimentation and drug development.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
Cell Signaling or Signal Transduction, is the study of
the mechanisms that enable the transfer of
biological information. Signaling impinges on all
aspects of biology, from development to disease
and is of utmost importance to future drug
discovery (Johnston et al, 2006).
Many diseases, such as cancer, involve malfunction
of signal transduction pathways.
Mathematical
modeling and simulation in this field has the
porpuse to help and guide the biologist in designing
experiments and generally to establish a conceptual
framework in which to think (Kitano et al, 2003).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
New modeling approaches involve the use of rules
to represent protein-protein interactions; rules are
also useful for representing other types of
biomolecular interactions.
The introduction of rules greatly eases the task of
specifying a model that incorporates details at the
level of protein sites.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
A rule—such as “ligand binds receptor with rate
constant k whenever ligand and receptor have free
binding sites”— describes the features of reactants
that are required for a particular type of chemical
transformation to take place.
Rules simplify the specification of a model when the
reactivity of a component in a system is determined
by only a subset of its possible features (Hlavacek et
al, 2006).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
Other authors propose that the concurrency
paradigm and the pi calculus theory are uniquely
suited to model and study biomolecular processes
in general and Signaling Transduction pathways in
particular.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
Table 1. Pi calculus modeling of typical molecular structures involved in Signaling
Transduction Pathways and key signaling events. (Shapiro et al, 2000).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
G Protein Signal Cascade
http://www.scribd.com/doc/48863/CELL-SIGNALING?autodown=pdf
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
G Protein Signal Cascade
http://www.scribd.com/doc/48863/CELL-SIGNALING?autodown=pdf
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
G Protein Signal Cascade
Lysozyme
insert
ligand
E.g., the b-adrenergic
receptor
is activated by
epinephrine &
norepinephrine.

-Adrenergic
Receptor
Most 7-helix receptors have
domains facing the
extracellular side of the
plasma membrane that
recognize & bind signal
molecules (ligands).
PDB 2RH1
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
G Protein Signal Cascade
G Protein Signal Cascade ANIMATION
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
The description of biological systems using concurrent
constraint processes involves a series of features that
can be beneficial to the interests of biology. These
features are based on the ability to represent:
(1) The evolution of systems over time (discrete or
continuous)
(2) Partial or incomplete behavioral information is
represented by non-deterministic and asynchronous
operators available in NTCC
(3) Partial quantitative information is captured by the
notion of constraint system, a structure that gives
coherence and defines (logic) inference capabilities over
constraints.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Signal-transduction pathways can be viewed as a
Reactive system that consists of parallel processes,
where each process may change state in reaction to
another process changing state, cells constantly
send and receive signals and operate under various
conditions simultaneously.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Signal-transduction pathways can be viewed as a
Nondeterministic system, that may have several
possible reactions to the same stimulus. Hence,
nondeterministic models capture the diverse
behavior often observed in Signal-transduction
pathways by allowing different choices of execution,
without assigning priorities or probabilities to each
choice.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Signal-transduction pathways can be viewed as a
Concurrent System, that consist of many processes
running in parallel and sharing common
resources.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Biological Description
G Protein Signal Cascade
Copyright © 1999-2008 by Joyce J. Diwan.
All rights reserved.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
hormone
signal
outside
GPCR
plasma
membrane
agga
AC
GDP GTP
GTP
GDP
cytosol
ATP cAMP + PPi
Turn on of the signal:
1. Initially Ga has bound GDP, and a,, and g subunits are
complexed together.
G,g, the complex of  & g subunits, inhibits Ga.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
hormone
signal
outside
GPCR
plasma
membrane
agga
AC
GDP GTP
GTP
GDP
cytosol
ATP cAMP + PPi
2. Hormone binding, usually to an extracellular domain of a 7-helix
receptor (GPCR), causes a conformational change in the receptor that
is transmitted to a G-protein on the cytosolic side of the membrane.
The nucleotide-binding site on Ga becomes more accessible to the
cytosol, where [GTP] > [GDP].
Ga releases GDP and binds GTP (GDP-GTP exchange).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
hormone
signal
outside
GPCR
plasma
membrane
agga
AC
GDP GTP
GTP
GDP
cytosol
ATP cAMP + PPi
3. Substitution of GTP for GDP causes another conformational
change in Ga.
Ga-GTP dissociates from the inhibitory g complex and can now
bind to and activate Adenylate Cyclase.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
hormone
signal
outside
GPCR
plasma
membrane
agga
AC
GDP GTP
GTP
GDP
cytosol
ATP cAMP + PPi
4. Adenylate Cyclase, activated by the stimulatory Ga-GTP,
catalyzes synthesis of cAMP.
5. Protein Kinase A (cAMP Dependent Protein Kinase) catalyzes
transfer of phosphate from ATP to serine or threonine residues of
various cellular proteins, altering their activity.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Turn off of the signal:
1. Ga hydrolyzes GTP to GDP + Pi. (GTPase).
The presence of GDP on Ga causes it to rebind to the
inhibitory g complex.
Adenylate Cyclase is no longer activated.
2. Phosphodiesterases catalyze hydrolysis of
cAMP  AMP.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
Signal amplification is an important feature of signal cascades:
 One hormone molecule can lead to formation of many
cAMP molecules.
 Each catalytic subunit of Protein Kinase A catalyzes
phosphorylation of many proteins during the life-time of
the cAMP.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why to develop a model by using NTCC calculus?
The goal will be find an appropriate NTCC model for
G Protein Signal Cascade (Signal Transduction
Pathway) that include molecular structure, behavior
and biological formal semantics.
What kind of expected results we are thinking to
obtain: a unified view of structure and dynamics of G
Protein Signal Cascade, a detailed molecular
information
(complexes,
molecules,
domains,
residues) in visible form, a complex dynamic
behavior (feedback, cross-talk, split and merge), a
modular system.
For more details and References, please visit:
http://dianahermith.phipages.com/research/
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions