Molecular Interaction Maps and Analysis of Bioregulatory Networks

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This project is performed in close collaboration with Dr. Kohn?s group in LMP and consists of two lines of study. First, we have recently developed and released several tools for creating and editing MIM diagrams (Luna, Karac et al. 2011; Luna, Sunshine et al. 2011; Chandan et al., 2012). These tools should make it easier for developers to build MIM-related software, users to create and edit MIM diagrams, and also, help bridge differences between features found in MIM and related notations, such as the BioPAX exchange standard (Demir et al., 2010) and the systems biology graphical notation (SBGN) that is developed by an international consortium with our participation (Le Novere, Hucka et al. 2009; van Iersel et al., 2012). We use MIMs as a basis for mathematical modeling of cellular regulatory networks in an effort to shed light on basic feedback mechanisms that modulate cell proliferation. The first network we have investigated describes the regulation of tumor suppressor p53 by Mdm2 and MdmX in response to DNA damage (Kim, Aladjem et al. 2010). The simplified network model was derived from a detailed molecular interaction map (MIM) that exhibited four coherent DNA damage response pathways. The results suggest that MdmX may amplify or stabilize DNA damage-induced p53 responses via non-enzymatic interactions. These studies led us to suggest a possible role of MdmX in the response of p53 to DNA damage. This model is currently under experimental investigation using a system in which the transcriptional activity of p5 can be directly visualized. In a separate line of study we have created an extended computational model of a mammalian circadian clock that emphasizes the roles of chromatin remodeling and metabolic pathways on the regulation of circadian rhythms. This model incorporates recent experimental evidence suggesting a role for the nicotinamide adenine dinucleotide (NAD+)-dependent histone deacetylase SIRT1 in regulating circadian rhythms. Simulation studies using the molecular interaction network included in the model were able to recapitulate circadian behavior. Development and analysis of this model will provide insights into the regulation of circadian rhythms and the potential role of SIRT1 in cancer biology. In the future we aim to combine these studies with experimental characterization of cell cycle regulatory networks that modulate DNA synthesis and affect cell growth. Results from these studies may also add to knowledge on the role of circadian rhythms on the toxicity and activity of therapeutics, including common cancer drugs. Tools to create and edit molecular interaction maps are essential for the acceptance and adoption of the methodology. This year we have expanded the repertoire of tool support available for the notation as well as contributed to the support of SBGN, a community effort to develop a graphical notation for systems biology.