* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download research title proposal - Pontificia Universidad Javeriana, Cali
Survey
Document related concepts
Cytokinesis wikipedia , lookup
Cell membrane wikipedia , lookup
Protein moonlighting wikipedia , lookup
Endomembrane system wikipedia , lookup
Multi-state modeling of biomolecules wikipedia , lookup
Protein phosphorylation wikipedia , lookup
Nuclear magnetic resonance spectroscopy of proteins wikipedia , lookup
Protein–protein interaction wikipedia , lookup
Biochemical cascade wikipedia , lookup
Paracrine signalling wikipedia , lookup
List of types of proteins wikipedia , lookup
Transcript
GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ Using a Timed Concurrent Constraint Process Calculus for Modeling Signal Transduction Systems (Graduate Research Draft Proposal) Diana Hermith, BSc. In Molecular Biology Graduate Student Program in Engineering Emphasis in Computer Systems [email protected] Research in Avispa: Concurrency Theory and ApplicationsPontificia Universidad Javeriana, Cali Cali (Colombia), Tuesday January 13th 2009 ABSTRACT Most 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. Metabolic pathways provide us with many examples of these kind of interactions. These molecules have an extracellular domain, a membrane domain, and an intracellular domain. The association of the corresponding intracellular domains allows the molecule to transmit the signal inside the cell. The number of proteins and other molecules participating in the events involving signal transduction increases as the process emanates from the initial stimulus, resulting in a "signal cascade," beginning with a relatively small stimulus that elicits a large response. We are planning gain a comprehensive and predictive understanding of the dynamic, interconnected processes underlying living systems, in these case, the G Protein Signal Cascade, with a NTCC model that could resolve some biological queries. The first goal would be, identify and characterize the biomolecular machinery of G Protein Signal Cascade as concurrent computation, using process algebra: the NTCC calculus. The second one, develop the computational capabilities to advanced understanding of complex biological systems and predict their behavior. 1 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ interactions, one protein affects another CONTENTS protein by, for example, regulating its I. Introduction 2 expression or changing the concentration of a factor that, in turn, is sensed by the target II. State of the Art (Short) 4 protein. The two modes of interaction are not exclusive. III. Detailed Description of the G Protein Signal Cascade The same proteins can interact both physically and logically.1 5 Metabolic pathways provide us with many IV. Why to develop a model by using examples of logical interactions. NTCC calculus? concentration of a product is often “sensed” 8 The by other proteins in its synthetic cascade References 14 and modulates their activity. The presence of hormones is detected by cell surface receptors and transmitted to other proteins I. INTRODUCTION in the cell that can interact with the genetic Most of biological functions are mediated material to activate or repress genes. These by protein interactions. These interactions logical can be physical, such as when two proteins physical form a complex, or “logical,” such as when hemoglobin senses the binding of oxygen one or more proteins control the behavior of and transmits the information from one of one or more other proteins without physical its subunits to the others via physical interaction. physical interaction. Other examples can be found interactions are stable complexes, in which in cell surface receptors. These molecules the functional unit is formed by more than have an extracellular domain, a membrane one protein chain, as in the case of the domain, and an intracellular glycogen and Binding of a ligand to the extracellular transient associations, in which the protein domain can cause these molecules to form Examples phosphorylase of enzyme, interactions interactions. can coexist For with example, domain. chains are stable by themselves but can also interact to transmit a signal or as a response to external conditions. In logical 1 Anna Tramontano. The Ten Most Wanted Solutions in Protein Bioinformatics. Anna Tramontano Chapman & Hall/CRC; ISBN: 1584884916; 216pp.; 2005. 2 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ dimers (i.e., to associate with another the order of milliseconds in the case of ion receptor chain). flux, or minutes for the activation of The association of the corresponding intracellular domains allows protein- and lipid-mediated kinase the molecule to transmit the signal inside cascades, but some can take hours, and the cell (Figure 1). even days (as is the case with gene expression), to complete. The number of proteins and other molecules participating in the events involving signal transduction increases as the process emanates from the initial stimulus, resulting in a "signal cascade," beginning with a relatively small stimulus that elicits a large response. This is referred to as amplification of the signal.2 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 interaction protein). between The the subsequent intracellular domains can trigger signaling, for example, by activating a transcription factor that, in turn, activates the required genes. 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. 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 Fig 2. Signal Transduction enzymes, activated by second messengers, resulting in a signal transduction pathway. Such processes are usually rapid, lasting on 2 http://en.wikipedia.org/wiki/Signal_transduction 3 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ II. STATE OF THE ART (Short) Thus, in addition to our curiosity about the Cell Signaling or Signal Transduction, is fascinating mechanism that cells use to the study of the mechanisms that enable the respond to signals, there is practical transfer information. motivation to better understanding the Signaling impinges on all aspects of processes of cellular signaling, in wich biology, from development to disease. protein-protein interactions play a central Many diseases, such as cancer, involve role. of malfunction pathways. biological of signal transduction Mathematical modeling and The behavior of a signal-transduction simulation in this field has the porpuse to system depends on dynamic interactions help and guide the biologist in designing among its proteins. The combined effects experiments and generally to establish a of these interactions are difficult to predict conceptual framework in which to think from intuition alone. (Kitano et al, 2003). insufficient, a mathematical model is often When intuition is useful for acquiring a quantitative and G-proteins represent a crucial family of predictive understanding of a complex signal transduction molecules that govern a dynamical variety functions. modeling is being increasingly used to aid Moreover, GPCRs have traditionally been in studies of cellular signaling. However, (and continue to be) a major exploitable current models are still far from capturing drug target, giving rise to a plethora of all of the relevant mechanistic details of clinically relevant molecules. Thus, a more signal-transduction systems that must be complete understanding of the fundamental considered to provide realistic and complete properties of GPCRs and how they interact pictures of how these systems work. with, and activate, their target G-proteins is particular, models often fail to account for of utmost importance to future drug the discovery (Johnston et al, 2006). interactions, such as how these interactions of physiological system, complexities and of mathematical In protein-protein depend on contextual details at the level of How GPCRs operate is one of the most protein sites. fundamental questions in the field of that address this problem involve the use of transmembrane signal transduction. rules to New modeling approaches represent protein-protein 4 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ interactions, rules are also useful for modification is modeled as communication representing other types of biomolecular and the subsequent change of channel interactions. names. Based on these three principles the pi calculus allows to fully represent The introduction of rules greatly eases the complex molecular structures and signaling task of specifying a model that incorporates events (Table 1) (Shapiro et al, 2000). 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). Table 1. Pi calculus modeling of typical Other authors propose that the concurrency molecular structures involved in Signaling paradigm and the pi calculus theory are Transduction Pathways and key signaling uniquely suited to model and study events. biomolecular processes in general and Signaling Transduction pathways in III. DETAILED DESCRIPTION OF particular. Within the particular framework THE G PROTEIN SIGNAL CASCADE3 of the pi calculus, they set three principles Most signal molecules targeted to a cell for this correspondence; first, as primitive bind at the cell surface to receptors process, functional embedded in the plasma membrane. Only signaling domain. Second, they model the signal molecules able to cross the plasma they component choose residues the of domains as communication channels that construct a process. Finally, molecular interaction and 3 http://www.rpi.edu/dept/bcbp/molbiochem/MB Web/mb1/part2/signals.htm#animat1 5 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ membrane (e.g., steroid hormones) interact include: altered ligand affinity, receptor with intracellular receptors. A large family dimerization or oligomerization, control of of cell surface receptors have a common receptor localization, including transfer to structural motif, 7 transmembrane - or removal from the plasma membrane, helices. Rhodopsin was the first of these to promoting close association with other have its 7-helix structure confirmed by X- signal proteins. ray crystallography. G-proteins are heterotrimeric, with 3 Rhodopsin is unique. It senses light, via a subunits , , . A G-protein that activates bound chromophore, retinal. Most 7-helix cyclic-AMP formation within a cell is receptors the called a stimulatory G-protein, designated extracellular side of the plasma membrane Gs with alpha subunit Gs. Gs is activated, that recognize and bind signal molecules e.g., by receptors (ligands). For example., the -adrenergic epinephrine receptor is activated by epinephrine and adrenergic receptor is the GPCR for norepinephrine. epinephrine. The signal is usually passed from a 7-helix hormone signal have domains facing and for the glucagon. hormones The - receptor to an intracellular G-protein. outside Seven-helix receptors are thus called GPCR, or G-Protein-Coupled Receptors. GPCR Approx. 800 different GPCRs are encoded plasma membrane AC GDP GTP in the human genome. GTP G-protein-Coupled Receptors may dimerize GDP cytosol ATP cAMP + PPi Fig. 3 The G Protein Signal Cascade4 or form oligomeric complexes within the membrane. Ligand binding may promote The subunit of a G-protein (G) binds oligomerization, which may in turn affect GTP, and can hydrolyze it to GDP + Pi.. activity of the receptor. Various GPCRinteracting proteins receptor function. (GIPs) modulate Effects of GIPs may 4 Molecular tinkering of G protein-coupled receptors: an evolutionary success”. The EMBO Journal Vol. 18 No. 7 pp. 1723-1729, 1999. 6 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ and subunits have covalently attached Phase 4. Adenylate Cyclase, activated by lipid anchors that bind a G-protein to the the plasma synthesis of cAMP. membrane Adenylate cytosolic Cyclase transmembrane protein, (AC) with surface. is stimulatory G.-GTP, catalyzes a cytosolic domains forming the catalytic site. Phase 5. Protein Dependent Kinase Protein Kinase) A (cAMP catalyzes transfer of phosphate from ATP to serine or The sequence of events by which a threonine residues of various cellular hormone activates cAMP signaling include proteins, altering their activity. the following phases: The turn off of the signal involves these Phase 1. Initially G has bound GDP, and kind of possibilities: and subunits are complexed together. G, the complex of and subunits, P1. G hydrolyzes GTP to GDP + Pi. inhibits G. (GTPase). The presence of GDP on G causes it to rebind to the inhibitory bg Phase 2. Hormone binding, usually to an complex. Adenylate Cyclase is no longer extracellular domain of a 7-helix receptor activated. (GPCR), causes a conformational change in the receptor that is transmitted to a G- P2. Phosphodiesterases catalyze hydrolysis protein on the cytosolic side of the of cAMP AMP. membrane. The nucleotide-binding site on G. becomes more accessible to the cytosol, P3. Receptor desensitization varies with the where [GTP] > [GDP]. G. releases GDP hormone. and binds GTP (GDP-GTP exchange). receptor is phosphorylated via a G-protein In some cases the activated Receptor Kinase. The phosphorylated Phase 3. Substitution of GTP for GDP receptor then may bind to a protein - causes another conformational change in arrestin. -Arrestin promotes removal of G.. G.-GTP dissociates from the the receptor from the membrane by inhibitory complex and can now bind to clathrin-mediated endocytosis. -Arrestin and activate Adenylate Cyclase. may also bind a cytosolic 7 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ Phosphodiesterase, bringing this enzyme IV. WHY TO DEVELOP A MODEL BY close to where cAMP is being produced, USING NTCC CALCULUS? contributing to signal turnoff. Partial information arises naturally in the description of biological systems. It is P4. Protein Phosphatase catalyzes removal possible to distinguish two main kinds of by hydrolysis of phosphates that were partial information when modeling those attached to proteins via Protein Kinase A. systems: While quantitative partial and behavioral. quantitative information The signal amplification is an important usually involves incomplete information on feature of signal cascades. One hormone the state of the system (e.g., the set of molecule can lead to formation of many possible values that a variable can take), cAMP molecules. Each catalytic subunit of partial behavioral information refers to the Protein Kinase A catalyzes phosphorylation uncertainty associated to behavior of many proteins during the life-time of the interactions (e.g., the unknown relative cAMP. speeds on which two systems interact). Different isoforms of G have For example, the Finding precise ways of expressing these when it binds GTP, kinds of partial information can help to different signal roles. stimulatory Gs activates Adenylate cyclase. An inhibitory Gi, when it binds GTP, inhibits Adenylate cyclase. of Different effectors and their better understand complex pattern behaviors, frequent in biological systems. Partial information is a central feature of Concurrent Constraint Programming receptors induce Gi, to exchange GDP for (CCP), a well-established formalism for GTP than those that activate Gs. concurrency. complex of G The In CCP, processes interact that is released when G with each other by telling and asking partial binds GTP is itself an effector that binds to information represented as constraints (e.g., and activates or inhibits several other x < 42). Perhaps the most appealing and proteins. For example, G inhibits one of several isoforms of Adenylate Cyclase, contributing to rapid signal turnoff in cells that express that enzyme. distinctive feature of CCP is that it combines the traditional operational view of process calculi with a declarative one based upon logic. In other words, the process terms can be viewed at the same time as 8 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ computing agents and logic formulas. This about the uncertainty in the occurrence time combination allows CCP to benefit from of many biological phenomena (Gutierrez the large body of techniques of both process et al, 2006). calculi and logic. For these reasons CCP can be a convenient framework to describe Signal-transduction and reason about biological systems. viewed as a molecular circuit. We begin by In challenges can posed be this paper we propose works with ntcc, a examining timed process calculus based on CCP, as a transferring extracellular information to a suitable language for analyzing biological cell's interior: systems. the pathways by In ntcc the above-mentioned kinds of partial information are naturally Phase 1. Membrane receptors transfer captured. On the one hand, partial information from the environment to the quantitative information is captured by the cell's interior. A few nonpolar signal notion of constraint system, a structure that molecules such as estrogens and other gives (logic) steroid hormones are able to diffuse through constraints. the cell membranes and, hence, enter the Since constraint systems are parametric to cell. Once inside the cell, these molecules ntcc, by choosing the appropriate constraint can bind to proteins that interact directly system(s) several kinds of conditions, at with DNA and modulate gene transcription. different levels of detail, can be stated. Thus, a chemical signal enters the cell and This could be particularly useful in the directly alters gene-expression patterns. coherence inference and capabilities defines over description of quantitative information. For instance, one could think of a constraint However, most signal molecules are too system equations large and too polar to pass through the interacting with others over, say, integers or membrane, and no appropriate transport real intervals. On the other hand, partial systems are present. Thus, the information behavioral information is represented by that signal molecules are present must be non-deterministic asynchronous transmitted across the cell membrane operators available in ntcc. The interplay of without the molecules themselves entering these operators in the discrete time of ntcc the cell. A membrane-associated receptor over differential and allows to explicitly describe and reason 9 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ protein often performs the function of cyclic GMP, calcium ion, inositol 1,4,5- information transfer across the membrane. trisphosphate, (IP3), and diacylglycerol. Such a receptor is an intrinsic membrane The use of second messengers has several protein that has both extracellular and consequences. First, second messengers are intracellular domains. A binding site on the often free to diffuse to other compartments extracellular domain specifically recognizes of the cell, such as the nucleus, where they the signal molecule (often referred to as the can influence gene expression and other ligand). Such binding sites are analogous processes. to enzyme active sites except that no amplified significantly in the generation of catalysis takes place within them. The second messengers. Enzymes or membrane interaction of the ligand and the receptor channels are almost always activated in alters the tertiary or quaternary structure of second-messenger the receptor, including the intracellular activated macromolecule can lead to the domain. These structural changes are not generation of many second messengers sufficient to yield an appropriate response, within the cell. Thus, a low concentration because they are restricted to a small of signal in the environment, even as little number of receptor molecules in the cell as a single molecule, can yield a large membrane. The information embodied by intracellular signal and response. Third, the the presence of the ligand, often called the use of common second messengers in primary messenger, must be transduced into multiple signaling pathways creates both other forms that can alter the biochemistry opportunities and potential problems. Input of the cell. from several signaling pathways, often called Phase 2. information Second from messengers the relay Second, the signal may be cross generation; talk, concentrations of may each affect common the second receptor-ligand messengers. Cross talk permits more finely complex. Changes in the concentration of tuned regulation of cell activity than would small molecules, called second messengers, the constitute the next step in the molecular pathways. information circuit. Particularly important talk can cause second messengers to be second messengers include cyclic AMP and misinterpreted. action of individual independent However, inappropriate cross 10 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ Phase 3. Protein phosphorylation is a signaling common means of information transfer. terminated Many second messengers elicit responses uncontrolled cell growth and the possibility by activating protein kinases. of cancer. These processes that properly fail may to be lead to enzymes transfer phosphoryl groups from ATP to specific serine, threonine, and As we shall see, the use of protein modules tyrosine residues in proteins. in various combinations is a clear, even dominant, theme in the construction of We previously encountered the cAMP- signal-transduction dependent protein kinase. This protein transduction proteins have evolved by the kinase and others are the link that addition of such ancillary modules to core transduces changes in the concentrations of domains to facilitate interactions with other free second messengers into changes in the proteins or cell membranes. By controlling covalent structures of proteins. Although which proteins interact with one another, these changes are less transient than the these modules play important roles in changes determining the wiring diagrams for signal- in secondary-messenger concentrations, protein phosphorylation is not irreversible. phosphatases are Indeed, proteins. Signal- transduction circuits. protein enzymes that (Bockaert, 1999) G protein coupled hydrolytically remove specific phosphoryl receptors (GPCRs; 7TM receptors; seven groups from modified proteins. transmembrane domain receptors; heptahelical receptors; G proteinlinked Phase 4. The signal is terminated. Protein receptors [GPLR]) are the largest family of phosphatases are one mechanism for the transmembrane termination of a signaling process. After a accounting for more than 1% of the protein signaling process has been initiated and the coding capacity of the human genome. All information has been transduced to affect known other cellular processes, the signaling architecture of seven membrane spanning processes must be terminated. helices connected by intra and extracellular such termination, cells Without lose GPCRs receptors share in a humans, common their loops. The extracellular loops contain two responsiveness to new signals. Moreover, highly conserved cysteine residues that 11 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ form disulphide bonds to stabilize the Signal transduction pathways allow cells to structure of the receptor. They recognize respond to environmental signals. In these diverse messengers such as light, odorants, pathways, a signal is amplified such that small and each step in the pathway results in a large Most GPCRs act as number of activated components than in the molecules, neurotransmitters. guanine hormones nucleotide factors; exchange previous step. This phenomenon, called activated by ligand binding, they promote signal amplification, caused the liver cell GDP associated for example, to release a significant number heterotrimeric guanine nucleotide binding of glucose molecules after detecting just a (G) proteins. These in turn activate effector single enzymes or ion channels. GPCRs are Amplification can occur at many points in involved in a range of physiological roles the pathway. which include the visual sense, smell, epinephrine remains bound to the receptor, behavioural regulation, functions of the the receptor can activate a succession of G autonomic nervous system and regulation proteins. In addition, each adenylyl cyclase of the immune system and inflammation. enzyme can convert numerous ATPs into GPCRs are divided into 6 classes based on cyclic AMP molecules. sequence enzymes GTP exchange homology on and functional molecule in of epinephrine. For example, as long as the Other activated pathway can also similarity; the main mammalian families continually are component that activates just a single classes A/1 C/3. (From www.reactome.com) catalyze reactions. One enzyme, however, is the G protein. A G protein must remain attached to the Class A/1 (Rhodopsin like) adenylyl cyclase enzyme in order for the Class B/2 (Secretin receptor family) enzyme to remain activated. Class C/3 (Metabotropic glutamate/pheromones) Termination of the cellular response is an Class D/4 (fungal mating pheromone important as its initiation. In order for a receptors) cell to respond only when a signal is Class E/5 (cAMP receptors) present, the many players in the pathway Class F/6 (Frizzled/Smoothened) have to regulated so that they are activate for only a short period of time. 12 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ We are planning, gain a comprehensive and understanding of complex biological predictive understanding of the dynamic, systems and predict their behavior. interconnected processes underlying living systems, in these case, the G Protein Signal Previous Cascade. For these purpose, is necessary to concurrent computational processes, each have biological entity is a process that may carry information about dynamics, abstractions state interacts that with in molecular structure and biochemical detail some of each interaction, to explore and apply processes. formal semantics to simulate, analyze and process algebras, such as the pi calculus can compare the biomolecular G Protein Signal be Cascade System. So in these first draft, we reasoning about this kind of systems. applied and shows, other Prior proposals5 based on for make an appropiate not yet include, the computational model, but we now, that the molecules involves in The benefits of the NTCC approach should the be an unified view of the system, the signal capability, pathways have interaction reactions/interactions and simulation and analysis and a comparative modification, with the same principles came power and scalability to enrich the model from chemistry, with experimental (quantitative) data. The enzymatic reactions, metabolic pathways, idea in this sense, is to explore and combine signal-transduction pathways and ultimately the metodology with implementations than the entire cell. Biology is driven by permit an interplay between collecting data quantities (e.g., energy, time, affinity, in experiments (experimental biology) and distance, amount of components) so we the NTCC model, with the aim to capture would need to consider this. some mechanistic understanding of how the chemistry, organic systems under study works, by validating The goal 1 would be, identify and the model under various conditions that characterize the biomolecular machinary of correspond to the experiments and by G Protein Signal Cascade as concurrent comparing computation, using Process algebra: the experimental NTCC calculus. The second one, develop discrepancies the computational capabilities to advance the outcomes data, one between to can the identify hypothetical 5 Regev et al. 2001. http://www.wisdom.weizmann.ac.il/~udi/papers /pi_calculus.pdf 13 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ mechanisms and experimental role of -arrestin?. How we can describe observations. These differences can be the activation of cAMP-Dependent Protein used to suggest new hypotheses, which Kinase (Protein Kinase A)?. What causes serve to adjust the model and need to be the enzyme to be inhibited in the absence of validated cyclic AMP?. How is activation by cyclic the experimentally, or new experiments, which can confirm or falsify AMP turned off?. What reaction is the modeling hypotheses. catalyzed enzyme The goal will be find an appropriate model Phosphatase?. by the Protein for G Protein Signal Cascade that include molecular structure, behavior and biological REFERENCES formal semantics. xpected results we are thinking to obtain: a unified view of structure and dynamics of G Protein Signal molecular Cascade, information a detailed (complexes, molecules, domains, residues) in visible form, a complex dynamic behavior [1] Executable Cell Biology. Jasmin Fisher and Thomas A Henzinger. Nature Biotechnology, volume 25 number 11 november 2007. [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). (feedback, cross-talk, split and merge), a modular system. We want construct a NTCC model that [3] Anna Tramontano. The Ten Most Wanted Solutions in Protein Bioinformatics. Anna Tramontano Chapman & Hall/CRC; ISBN: 1584884916; 216pp.; 2005. could resolve some of these biological queries: describe the sequence of events by which a hormone such as epinephrine or glucagon activates production of cyclic AMP within a cell; include the roles of the receptor (GPCR), the different subunits of the stimulatory G protein, and Adenylate Cyclase. How is the signal turned off at [4] Representation and simulation of biochemical processes using the pi-calculus process algebra. A Regev, W Silverman, E Shapiro. 2001. http://www.wisdom.weizmann.ac.il/~udi/pa pers/pi_calculus.pdf [5] Timed Concurrent Constraint Programming in Systems Biology. A. Arbelaez, J. Gutierrez, J. Perez. http://avispa.puj.edu.co each step?. How we can be simulate the 14 GRADUATE PROGRAM IN ENGINEERING RESEARCH TITLE PROPOSAL: USING A TIMED CONCURRENT CONSTRAINT PROCESS CALCULUS FOR MODELING BIOMOLECULAR INTERACTIONS Research in Avispa: Concurrency Theory and Applications Cali (Colombia), Tuesday January 13th, 2009 ______________________________________________________________________ [6] Timed Concurrent Constraint Programming for Analysing Biological Systems. J. Gutierrez, J. Perez, C. 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). [13] Rules for Modeling SignalTransduction Systems. W. Hlavacek, J. Faeder, M. Blinov, R. Posner, M. Hucka, W. Fontana. Sciences STKE, 2006. [14] The Complexity of Complexes in Signal Transduction. William S. Hlavacek, James R. Faeder, Michael L. Blinov, Alan S. Perelson,Byron Goldstein. Biotechnology and Bioengineering, Vol. 84, No. 7, December 30, 2003, 783-794 pp. [15] Formal Methods for Biochemical Signalling Pathways. Mu.y Calder, Stephen Gilmore, Jane Hillston and Vladislav Vyshemirsky. http://homepages.inf.ed.ac.uk/jeh/papers.ht ml [9] Systems Biology: Looking at opportunities and challenges in applying systems theory to molecular and cell biology. O. Wolkenhauer, H. Kitano and KH Cho. IEEE Control Systems Magazine, August 2003. [10] Computing in Molecular Biology: Mapping and Interpreting Biological Information. E. Lander, R. Langridge and D. Saccocio. IEEE Control Systems Magazine, November 1991. [11] Computational Approaches to Discovering Semantics in Molecular Biology. R. Lipton, T. Marr and D. Welsh. Proceedings ot the IEE, Vol. 77, No. 7, July 1989. [12] Resolving G protein-coupled receptor signaling mechanics in vivo using fluorescent biosensors. C. Johnston, D. Siderovski. CellScience Reviews, Vol.2, No. 3, 2006. 15