MSM: Modeling Spatial Formation of Cellular Components *

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DESCRIPTION (provided by applicant): T cell activation underlies the adaptive immune response, and an understanding of how this is regulated has many potential benefits including production of better vaccines and treatment of autoimmune diseases. T cell activation is predicated on the binding of the T cell receptor to cognate ligands on antigen presenting cells. This interaction can stimulate intracellular signaling cascades that ultimately lead to the upregulation of gene transcription factors. Recently, it has been demonstrated that spatial organization of membrane-associated molecules and intracellular signaling components plays a role in regulating T cell signaling. T-cell activation is an emergent property that results from collective dynamics involving interactions between multiple components. This inherent cooperativity and the complex spatial organization that can regulate the collective dynamics makes it difficult to intuit mechanistic insights from experimental data alone, and progress requires mathematical models that integrate phenomena ranging from molecular size and time scales to cellular scales. To address how spatial organization of cellular components influences T cell response to external stimuli, our proposed research includes four specific aims that bridge multiple scales: (1) Develop hybrid Molecular dynamics/Brownian dynamics methods that will enable the study of dynamical events leading to spatial localization of multimeric protein complexes that mediate signaling initiated by receptor engagement, (2) Develop models that can describe cytoskeletal dynamics triggered by intracellular signaling and those involved in endocytosis of cell surface receptors, (3) Develop efficient algorithms that can treat the stochastic dynamics of signaling reactions in a spatially heterogeneous and crowded molecular environment, and will require the creation of hybrid methods combining stochastic and mean-field descriptions. (4) While each of the above specific aims involves the development of new methodology that in itself requires a bridging of scales, our fourth specific aim involves an overall integration of scales using specific aims 1 and 2 as necessary input for the coputations performed in specific aim 3. For example, models of cell signaling dynamics that will be developed in specific aim 3 require knowing whether a multimeric signaling complex forms sequentially or in a concerted fashion, which will be determined using the molecular scale methods developed in specific aim 1. The computational results will be tested directly against experiments.