Download G a - Pontificia Universidad Javeriana, Cali

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
Source:
Author: Kieran O'Neill A modern illustration of the 1970 version of the central dogma of
molecular biology, after the diagrams in the original article:
1970 Crick, F., Central Dogma of Molecular Biology. Nature 227, 561-563
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
http://www.scribd.com/doc/48863/CELL-SIGNALING?autodown=pdf
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Introduction
Most of biological functions are mediated by protein
interactions. These interactions can be physical,
such as when two proteins form a complex, or
“logical,” such as when one or more proteins control
the behavior of one or more other proteins without
physical interaction.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Introduction
Metabolic pathways provide us with many examples
of logical interactions. The concentration of a
product is often “sensed” by other proteins in its
synthetic cascade and modulates their activity.
The presence of hormones is detected by cell
surface receptors and transmitted to other proteins
in the cell that can interact with the genetic material
to activate or repress genes.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Introduction
In biology, signal transduction refers to any process
by which a cell converts one kind of signal or
stimulus into another.
Most processes of signal transduction involve
ordered sequences of biochemical reactions inside
the cell, which are carried out by enzymes, activated
by second messengers, resulting in a signal
transduction pathway.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Introduction
An environmental signal, such as a hormone, is first
received by interaction with a cellular component,
most often a cell-surface receptor. The information
that the signal has arrived is then converted into
other chemical forms, or transduced. The signal is
often amplified before evoking a response.
Feedback pathways regulate the entire signaling
process.
Signal Transduction
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.
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)
Thus, a more complete understanding of the
fundamental properties of GPCRs and how they
interact with, and activate, their target G-proteins is
of utmost importance to future drug discovery
(Johnston et al, 2006).
How GPCRs operate is one of the most fundamental
questions in the field of transmembrane signal
transduction.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
In particular, models often fail to account for the
complexities of protein-protein interactions, such as
how these interactions depend on contextual details
at the level of protein sites.
New modeling
approaches that address this problem involve the
use
of
rules
to
represent
protein-protein
interactions, rules are also useful for representing
other types of biomolecular interactions.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
State of the Art (Short)
The introduction of rules greatly eases the task of
specifying a model that incorporates details at the
level of protein sites. 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)
Within the particular framework of the pi calculus,
they set three principles for this correspondence;
first, as primitive process, they choose the
functional signaling domain. Second, they model
the
component
residues
of
domains
as
communication channels that construct a process.
Finally, molecular interaction and modification is
modeled as communication and the subsequent
change of channel names. Based on these three
principles the pi calculus allows to fully represent
complex molecular structures and signaling events
(Shapiro et al, 2000).
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.
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
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
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
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
G Protein Signal Cascade ANIMATION
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
Partial information arises naturally in the description
of biological systems. It is possible to distinguish
two main kinds of partial information when
modeling
those
systems:
quantitative
and
behavioral.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
While partial quantitative information usually
involves incomplete information on the state of the
system (e.g., the set of possible values that a
variable can take), partial behavioral information
refers to the uncertainty associated to behavior of
interactions (e.g., the unknown relative speeds on
which two systems interact).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
In NTCC the above-mentioned kinds of partial
information are naturally captured. On the one
hand, 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 Models using NTCC Calculus
On the other hand, partial behavioral information is
represented by non-deterministic and asynchronous
operators available in ntcc.
The interplay of these operators in the discrete time
of ntcc allows to explicitly describe and reason
about the uncertainty in the occurrence time of
Signal-transduction pathways.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models 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 Models 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 Models 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 Models using NTCC Calculus
Biological Description
Copyright © 1999-2008 by Joyce J. Diwan.
All rights reserved.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
hormone
signal
outside
GPCR
plasma
membrane
a g
GDP b
GTP
GDP
g  a
AC
b
GTP
cytosol
ATP cAMP + PPi
Turn on of the signal:
1. Initially Ga has bound GDP, and a, b, & g subunits are complexed
together.
Gb,g, the complex of b & g subunits, inhibits Ga.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
hormone
signal
outside
GPCR
plasma
membrane
a g
GDP b
GTP
GDP
g  a
AC
b
GTP
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 & binds GTP (GDP-GTP exchange).
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
hormone
signal
outside
GPCR
plasma
membrane
a g
GDP b
GTP
GDP
g  a
AC
b
GTP
cytosol
ATP cAMP + PPi
3. Substitution of GTP for GDP causes another conformational
change in Ga.
Ga-GTP dissociates from the inhibitory bg complex & can now
bind to and activate Adenylate Cyclase.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models using NTCC Calculus
hormone
signal
outside
GPCR
plasma
membrane
a g
GDP b
GTP
GDP
g  a
AC
b
GTP
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 Models 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 bg 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 Models using NTCC Calculus
3. Receptor desensitization varies with the hormone.
• In some cases the activated receptor is phosphorylated via a Gprotein Receptor Kinase.
• The phosphorylated receptor then may bind to a protein
b-arrestin.
• b-Arrestin promotes removal of the receptor from the membrane
by clathrin-mediated endocytosis.
• b-Arrestin may also bind a cytosolic Phosphodiesterase,
bringing this enzyme close to where cAMP is being produced,
contributing to signal turnoff.
4. Protein Phosphatase catalyzes removal by hydrolysis of
phosphates that were attached to proteins via Protein
Kinase A.
Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions
Why Models 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 Models using NTCC Calculus
The goal will be find an appropriate NTCC model for
G Protein Signal Cascade 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