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COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
Modeling Biomolecular Interactions with NTCC Process Calculi
(Draft Proposal)
Hermith, Diana
[email protected]
INTRODUCTION
physically and logically.
Most biological functions are mediated
which proteins interact, how they do so,
by
These
and what function is performed by their
interactions can be physical, such as
complex is at least as important as
when two proteins form a complex, or
predicting
“logical,” such as when one or more
structure
proteins control the behavior of one or
Historically, the problem of detecting
more other proteins without physical
the site where two proteins (or a protein
interaction.
Examples of physical
and a nucleic acid molecule) interact
interactions are stable complexes, in
has been treated separately from the
which the functional unit is formed by
problem of finding where a small
more than one protein chain, as in the
molecule such as an inhibitor or a
case of the glycogen phosphorylase
substrate binds to a macromolecule.
enzyme, and transient associations, in
The two cases are similar only at a first
which the protein chains are stable by
glance; they differ quite substantially in
themselves but can also interact to
the details of the techniques.1
protein
interactions.
the
of
Detecting
threedimensional
individual
proteins.
transmit a signal or as a response to
external
conditions.
logical
Metabolic pathways provide us with
interactions, one protein affects another
many examples of logical interactions.
protein by, for example, regulating its
The concentration of a product is often
expression
the
“sensed” by other proteins in its
concentration of a factor that, in turn, is
synthetic cascade and modulates their
sensed by the target protein. The two
activity. The presence of hormones is
modes of interaction are not exclusive.
1
or
In
changing
The same proteins can interact both
Anna Tramontano. The Ten Most Wanted
Solutions in Protein Bioinformatics. Anna
Tramontano Chapman & Hall/CRC; ISBN:
1584884916; 216pp.; 2005.
1
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
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.
External stimuli, such as the presence of
food or poison, is sensed by a bacterium
and transmitted to its flagella to direct
the cell towards or away from the
region of highest concentration of the
sensed
substance.
These
logical
interactions can coexist with physical
interactions. For example, hemoglobin
senses the binding of oxygen and
transmits the information from one of
its subunits to the others via physical
interaction.
Other examples can be
found in cell surface receptors. These
molecules have an extracellular domain,
a
membrane
domain,
and
an
intracellular domain.
Fig. 1. The binding of a ligand to the
extracellular
domain
of
a
transmembrane receptor might cause its
binding to a coreceptor (which can be
the same or a different protein). The
subsequent interaction between the
intracellular domains can trigger
signaling, for example, by activating a
transcription factor that, in turn,
activates the required genes.
Principles of Signal Transduction
In biology, signal transduction refers to
Binding of a ligand to the extracellular
domain can cause these molecules to
form dimers (i.e., to associate with
another
receptor
association
intracellular
of
chain).
the
domains
The
corresponding
allows
the
molecule to transmit the signal inside
the cell (Figure 1).
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
a
second
messengers,
signal
transduction
resulting
in
pathway.
Such processes are usually
2
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
rapid, lasting on the order of
milliseconds in the case of ion flux, or
minutes for the activation of proteinand lipid-mediated kinase cascades, but
some can take hours, and even days (as
is the case with gene expression), to
complete. The number of proteins and
other molecules participating in the
Fig 2. Signal Transduction
events involving signal transduction
increases as the process emanates from
Introduction to the Problem : G
the initial stimulus, resulting in a "signal
Protein Signal Cascade3
cascade," beginning with a relatively
small stimulus that elicits a large
Most signal molecules targeted to a cell
response.
bind at the cell surface to receptors
This is referred to as
amplification of the signal.2
embedded in the plasma membrane.
Only signal molecules able to cross the
An environmental signal, such as a
plasma
membrane
hormone, is first received by interaction
hormones) interact with intracellular
with a cellular component, most often a
receptors. A large family of cell surface
cell-surface receptor. The information
receptors have a common structural
that the signal has arrived is then
motif,
converted into other chemical forms,
Rhodopsin was the first of these to have
or transduced. The signal is often
its 7-helix structure confirmed by X-ray
amplified before evoking a response.
crystallography.
7
(e.g.,
transmembrane
steroid
-helices.
Feedback pathways regulate the entire
signaling process.
Rhodopsin is unique. It senses light, via
a bound chromophore, retinal. Most 7helix receptors have domains facing the
3
2
http://en.wikipedia.org/wiki/Signal_transduction
http://www.rpi.edu/dept/bcbp/molbiochem/MB
Web/mb1/part2/signals.htm#animat1
3
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
extracellular side of the plasma
G-proteins are heterotrimeric, with 3
membrane that recognize and bind
subunits , , .
signal
For
activates cyclic-AMP formation within
example., the -adrenergic receptor is
a cell is called a stimulatory G-protein,
activated
designated Gs with alpha subunit Gs.
molecules
by
(ligands).
epinephrine
and
norepinephrine.
A G-protein that
Gs is activated, e.g., by receptors for the
hormones epinephrine and glucagon.
The signal is usually passed from a 7-
The -adrenergic receptor is the GPCR
helix receptor to an intracellular G-
for epinephrine.
protein. Seven-helix receptors are thus
called GPCR, or G-Protein-Coupled
Receptors.
hormone
signal
Approx. 800 different
GPCRs are encoded in the human
outside
GPCR
plasma
membrane
genome.
G-protein-Coupled
Receptors

AC
GDP GTP
may
dimerize or form oligomeric complexes
within the membrane. Ligand binding
GTP
GDP
cytosol
ATP cAMP + PPi
Fig. 3 The G Protein Signal Cascade
may promote oligomerization, which
The  subunit of a G-protein (G) binds
may in turn affect activity of the
GTP, and can hydrolyze it to GDP + Pi..
receptor.
 and  subunits have covalently
proteins
Various GPCR-interacting
(GIPs)
modulate
receptor
attached lipid anchors that bind a G-
function. Effects of GIPs may include:
protein
altered
cytosolic surface.
ligand
affinity,
receptor
to
the
plasma
membrane
Adenylate Cyclase
dimerization or oligomerization, control
(AC) is a transmembrane protein, with
of
cytosolic domains forming the catalytic
receptor
localization,
including
transfer to or removal from the plasma
site.
membrane, promoting close association
with other signal proteins.
4
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
The sequence of events by which a
Phase 5. Protein Kinase A (cAMP
hormone activates cAMP signaling
Dependent Protein Kinase) catalyzes
include the following phases:
transfer of phosphate from ATP to
serine or threonine residues of various
Phase 1. Initially G has bound GDP,
cellular proteins, altering their activity.
and   and  subunits are complexed
together. G, the complex of  and 
The turn off of the signal involves these
subunits, inhibits G.
kind of possibilities:
Phase 2. Hormone binding, usually to
P1. G hydrolyzes GTP to GDP + Pi.
an extracellular domain of a 7-helix
(GTPase). The presence of GDP on G
receptor
causes it to rebind to the inhibitory bg
(GPCR),
causes
a
conformational change in the receptor
complex.
Adenylate Cyclase is no
that is transmitted to a G-protein on the
longer activated.
cytosolic side of the membrane. The
nucleotide-binding site on G. becomes
P2.
Phosphodiesterases
more accessible to the cytosol, where
hydrolysis of cAMP  AMP.
catalyze
[GTP] > [GDP]. G. releases GDP and
binds GTP (GDP-GTP exchange).
P3. Receptor desensitization varies with
the hormone.
In some cases the
Phase 3. Substitution of GTP for GDP
activated receptor is phosphorylated via
causes another conformational change
a G-protein Receptor Kinase.
in G.. G.-GTP dissociates from the
phosphorylated receptor then may bind
inhibitory  complex and can now bind
to a protein -arrestin.
to and activate Adenylate Cyclase.
promotes removal of the receptor from
The
-Arrestin
the membrane by clathrin-mediated
Phase 4. Adenylate Cyclase, activated
endocytosis. -Arrestin may also bind a
by the stimulatory G.-GTP, catalyzes
cytosolic Phosphodiesterase, bringing
synthesis of cAMP.
this enzyme close to where cAMP is
5
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
being produced, contributing to signal
proteins. For example, G inhibits
turnoff.
one of several isoforms of Adenylate
Cyclase, contributing to rapid signal
P4.
Protein
Phosphatase
catalyzes
removal by hydrolysis of phosphates
turnoff in cells that
express that
enzyme.
that were attached to proteins via
THE PROPOSAL:
Protein Kinase A.
Gain a comprehensive and predictive
The signal amplification is an important
understanding
of
the
dynamic,
feature of signal cascades.
interconnected
processes
underlying
hormone
molecule
can
lead
One
to
living systems, in these case, the G
formation of many cAMP molecules.
Protein Signal Cascade.
For these
Each catalytic subunit of Protein Kinase
purpose, is necessary to have some
A catalyzes phosphorylation of many
information about dynamics, molecular
proteins during the life-time of the
structure and biochemical detail of
cAMP.
interaction, to explore and apply formal
semantics to simulate, analyze and
Different isoforms of G have different
compare the biomolecular G Protein
signal
Signal Cascade System.
roles.
stimulatory Gs
activates
For
example,
the
when it binds GTP,
Adenylate
cyclase.
An
inhibitory Gi, when it binds GTP,
inhibits Adenylate cyclase.
Different
So in these
first draft, we not yet include, the
syntax, the structural congruece (bound
variables, laws) and reaction rules, but
we now, that the molecules involves in
the signal pathways have interaction
effectors and their receptors induce Gi,
capability (we can use the channel
to exchange GDP for GTP than those
abstracción),
that activate Gs.
(communication)
G
The complex of
that is released when G binds
GTP is itself an effector that binds to
and activates or inhibits several other
(state
and/or
reactions/interactions
and
modification
channel/conformational
change), with the same principles
specify chemistry, organic chemistry,
6
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
enzymatic
reactions,
metabolic
appropiate reasoning about this kind of
pathways, signal-transduction pathways
systems.
and ultimately the entire cell. Biology
is driven by quantities (e.g., energy,
The principles of modeling in NTCC
time, affinity, distance, amount of
calculus the G Protein Signal Cascade
components)
need
will be include the molecule as a
stochastic variant of NTCC process
computational process, the biochemical
algebras must be considered simulation
interaction as communication, the use of
techniques come into play.
process algebra to model the G Protein
so
we
would
Signal Cascade applying the NTCC
The goal 1 would be, identify and
process calculi.
characterize
biomolecular
approach should be an unified view of
machinary of G Protein Signal Cascade
the system, the simulation and analysis
as
using
and a comparative power and scalability
Process algebra: the NTCC calculus.
to enrich the model with experimental
The
(quantitative) data.
the
concurrent
second
computation,
one,
develop
the
The benefits of the
The idea in this
computational capabilities to advance
sense, is to explore and combine the
understanding of complex biological
metodology with implementations than
systems and predict their behavior.
permit an interplay between collecting
data
in
experiments
(experimental
Previous abstractions shows, that in
biology) and the NTCC model, with the
concurrent
aim
computational
processes,
to
capture
some
mechanistic
each biological entity is a process that
understanding of how the systems under
may carry some state and interacts with
study works, by validating the model
other processes. Prior proposals4 based
under
on process algebras, such as the pi
correspond to the experiments and by
calculus can be applied for make an
comparing
various
the
conditions
outcomes
that
to
the
experimental data, one can identify
4
Regev et al. 2001.
http://www.wisdom.weizmann.ac.il/~udi/papers
/pi_calculus.pdf
discrepancies
mechanisms
between
and
the
hypothetical
experimental
7
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
observations. These differences can be
•Message: Protein A phosphorylates a
used to suggest new hypotheses, which
residue on B
serve to adjust the model and need to be
•Meaning of message: This enables
validated
Protein B to bind to C
experimentally,
or
new
experiments, which can confirm or
xpected results we are thinking to
falsify the modeling hypotheses.
obtain: a unified view of structure and
The goal will be find an appropriate
dynamics of G Protein Signal Cascade,
model for G Protein Signal Cascade that
a
include molecular structure, behavior
(complexes,
and biological formal semantics.
residues) in visible form, a complex
detailed
molecular
information
molecules,
domains,
dynamic behavior (feedback, cross-talk,
Therefore it is necessary consider the
split and merge), a modular system.
molecule as a computational process,
represent a structure by its potential
We want construct a NTCC model that
behavior (by the process in which it can
could resolve some of these biological
participate). For example, an enzyme
queries: describe the sequence of events
(protein molecule) as the enzymatic
by
reaction process in which it may
epinephrine
participate.
It is also necessary, to
production of cyclic AMP within a cell;
consider
the
as
include the roles of the receptor
communication (molecular interaction
(GPCR), the different subunits of the
and modification as communication and
stimulatory G protein, and Adenylate
change
each
Cyclase. How is the signal turned off at
interaction enables or disables other
each step?. How we can be simulate the
interactions. For example, consider the
role of -arrestin?.
simple following model:
describe the activation of cAMP-
•A system: Proteins A, B, and C
Dependent
•Communication: Protein A and B can
Kinase A)?. What causes the enzyme to
interact
be inhibited in the absence of cyclic
of
interaction
channel
names),
which
AMP?.
a
or
hormone
glucagon
Protein
such
as
activates
How we can
Kinase
(Protein
How is activation by cyclic
8
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
AMP turned off?. How we can explain
overlap between the two proteins atoms;
the reaction catalyzed by the activated
that is, to treat each atom as a soft rather
cAMP-Dependent
Kinase?.
than a hard sphere so that limited
What reaction is catalyzed by the
interpenetration of the atoms of the two
enzyme Protein Phosphatase?.
proteins is allowed in the final docked
Protein
conformation.
For molecular structure considerations,
it is important think about the process of
BIBLIOGRAPHY
successful “docking”; it depends on
[1] Executable Cell Biology. Jasmin
Fisher and Thomas A Henzinger.
Nature Biotechnology, volume 25
number 11 november 2007.
three things: how we represent the
protein structures, taking into account
their flexibility; how we search the
conformational space of the possible
solutions; and how we evaluate and
rank the solutions. A protein structure,
and especially the side chains involved
in
binding,
substantial
can
undergo
rearrangements
formation of the complex.
[2]
Representing
Biomolecular
Processes with Computer Process
Algebra: Pi Calculus programs of
Signal Transduction pathways. Aviv
Regev, William Silverman and Ehud
Shapiro.
American Association for
Artificial Intelligence (www.aaai.org).
quite
upon
In some
cases, the observation of the protein
[3] Anna Tramontano. The Ten Most
Wanted
Solutions
in
Protein
Bioinformatics. Anna Tramontano
Chapman
&
Hall/CRC;
ISBN:
1584884916; 216pp.; 2005.
structure might suggest specific regions
that
are
likely
conformation
upon
to
modify
binding.
their
For
example, regions between domains can
be specifically allowed to assume a
discrete set of conformations. Another
possibility is to use a single-protein
structure conformation and introduce
the treatment of flexibility later in the
procedure, by not penalizing limited
[4] Representation and simulation of
biochemical processes using the picalculus process algebra. A Regev, W
Silverman,
E
Shapiro.
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http://www.wisdom.weizmann.ac.il/~ud
i/papers/pi_calculus.pdf
[5] Timed Concurrent Constraint
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http://avispa.puj.edu.co
[6] Timed Concurrent Constraint
Programming for Analysing Biological
Systems. J. Gutierrez, J. Perez, C.
9
COMPUTER SCIENCES MASTER PROGRAM
PROCESS COMPUTATIONAL MODELING COURSE
PROFESSOR: FRANK VALENCIA, PhD.
TITLE PROPOSAL:
MODELING BIOMOLECULAR INTERACTIONS WITH NTCC PROCESS CALCULI
Diana Hermith, BSc. Molecular Biology
Current Graduate Student in Computer Sciences
November 11th de 2008
______________________________________________________________________
Rueda
and
F.
Valencia.
http://www.elsevier.nl/locate/entcs
[7]
Modelamiento
de
Sistemas
Biológicos usando Cálculos de Procesos
Concurrentes. J. Gutierrez, J. Perez, C.
Rueda. Epiciclos. Cali (Colombia),
diciembre de 2005.
[8] A Calculus for Modelling,
Simulating
and
Analysing
Compartmentalized Biological Systems.
R. Mardare and A. Ihekwaba.
Computation in Modern Science and
Engineering: Proceedings of the
International
Conference
on
Computational Methods in Science and
Engineering 2007 (iccmse 2007): Vol.
2, parts A and B. AIP conference
proceedings, Vol 963, pp. 642-646
(2007).
[9] Systems Biology: Looking at
opportunities and challenges in applying
systems theory to molecular and cell
biology. O. Wolkenhauer, H. Kitano
and K-H Cho. IEEE Control Systems
Magazine, August 2003.
[10] Computing in Molecular Biology:
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Information. E. Lander, R. Langridge
and D. Saccocio.
IEEE Control
Systems Magazine, November 1991.
[11] Computational Approaches to
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