Modeling a biological transmembrane signaling system by using concurrent constraint process calculi

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Modeling a Biological Transmembrane Signaling System by Using Concurrent Constraint Process Calculi
Diana Hermith, and Camilo Rueda

One of the most recent area using computer science formalisms to explore and understand the complexity of biological systems and its further applications in biological engineering or drug design are the cellular signaling events or signaltransduction pathways. At the cellular level, molecular mechanisms to communicate with the environment involve many concurrent processes and relationships interacting with diverse signal molecules, which sense external information to control the flow of information in the cell over time. To address these concerns, this research proposal has two purposes: to understand the interactions and the behaviorof the cellular signaling processing information in the cell membrane and be able to compare it with other models from a biological point of view; and to analyze the advantages and possible limitations of using the concurrent constraint calculus (CCP) model to represent a biological transmembrane signaling process. Key Words—Concurrent constraint process calculi, cellsignaling pathways, molecularand computational systems biology modeling.

behavior of the machinery of the cellular signaling; and (iii) make a contribution at the level of molecular and pharmacological biology. Most of the biological functions are mediated by cell surface receptors, i.e., a protein-protein interaction between the receptor and its respective ligand (signaling molecule). The association and the interactionbetween them allow the transmition of the signal inside the cell. The interactions can be physical, such as when two proteins form a complex or “logical” for instance when one or more proteins control the behavior of one or more other proteins without physical interaction [2]. A large number of molecules and proteins take part in transmembrane signaling events, starting from a relatively small andinitial stimulus, resulting in a “signal cascade” or in a “signal transduction pathway” that elicits a large response. Diverse signaling molecules, including neurotransmitters, hormones, phospholipids, photons, odorants, taste ligands, and mitogen bind in the membrane of the target cells to their specific guanine nucleotide-binding protein-coupled receptors (GPCRs), also known asseven-transmembrane receptors (7TMRs) [3]. Subsequently, the receptors interact with their respective guanine proteins (G-proteins) to induce a cascade of downstream (i.e., transmembrane signaling). The main components and events are already well known, but the interactions with their respective G-proteins to induce an intracellular signaling are still not completely understood [4][11]. This is especially true foraspects like cellular specificity, i.e., the way in which the different parts of the signaling pathway become active as well as time dependencies of the activation. Cellular signaling -cellular information processing- is critical to the survival of all organisms and plays a key role in human health and disease. The use of process calculus to represent biochemical systems has become a common effortto obtain compositional and scalable representations of large biological systems [12][17]. Concurrent constraint programming (CCP) based process calculi has shown to be convenient for modeling, simulating, and verifying several kinds of biological systems [18]-[21]. It is considered that a (CCP) process calculus offers


he transmembrane cellular signaling system is a complexprocess with a rich network of multi-functional interactions that occurs in non-linear fashion. The molecular and computational systems biology promises a systemic approach to interpret and tackle the complexity of cellular signaling through the integration of biological information, applied mathematics and statistics with approaches and techniques of computer science [1]. Much effort has been...
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