Diana Hermith, BSc. Molecular Biology 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 13 th 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

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

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) (Shapiro et al, 2000). 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 Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions

G Protein Signal Cascade Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions

G Protein Signal Cascade Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions Most 7-helix receptors have domains facing the extracellular side of the plasma membrane that recognize & bind signal molecules (ligands). E.g., the b-adrenergic receptor is activated by epinephrine & norepinephrine.

G Protein Signal Cascade Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions G Protein Signal Cascade ANIMATION G Protein Signal Cascade ANIMATION

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 Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions Copyright © by Joyce J. Diwan. All rights reserved. Why to develop a model by using NTCC calculus?

Turn on of the signal: 1. Initially G  has bound GDP, and  and  subunits are complexed together. G , , the complex of  &  subunits, inhibits G . Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions Why to develop a model by using NTCC calculus?

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 G  becomes more accessible to the cytosol, where [GTP] > [GDP]. G  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?

3. Substitution of GTP for GDP causes another conformational change in G . G  -GTP dissociates from the inhibitory  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?

4. Adenylate Cyclase, activated by the stimulatory G  -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. G  hydrolyzes GTP to GDP + P i. (GTPase). The presence of GDP on G  causes it to rebind to the inhibitory  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 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: Using a Timed Concurrent Constraint Process Calculus for Modeling Biomolecular Interactions Why to develop a model by using NTCC calculus?