Development of computational models of signal transduction pathways implicated in colon cancer is proposed. These models give insight into the pathway's dynamical behavior and elucidate their roles in activating known oncogenic target genes. The project will model the Ras Map Kinase signal transduction pathway, which plays a central role in the development of colon cancer. The methods utilized, which will be further developed, combine computational modeling with experiments so that unknown parameters in the model are constrained. The goal is to create accurate, predictive models by combining the forward modeling approach with experimental data. The computational and experimental processes developed can be applied to other pathways implicated in colon cancer. Accurate computational models of signaling pathways will bring rational, predictive science to the drug discovery process and lead to effective therapies for colon cancer. These simulations will help pharmaceutical and biotechnology companies prioritize drug targets, test the effects of lead compounds, and focus and direct laboratory efforts.
Specific aims are (1) to develop a detailed mathematical and computational model of the Ras Map Kinase pathway; (2) to conduct experiments on pathway components to extract the data needed to constrain parameters in the model; (3) to use and devise optimization algorithms to constrain parameters in the model and (4) generate predictions from the model.
The research will provide an in silico simulation of the gene expression networks and signal transduction controlling the onset of colon cancer. New methods will be developed for incorporating data into the in silico platform generated by DNA microarrays, proteomics technologies, structural genomics, and protein-protein interaction studies to prioritize known drug targets. New mathematical analysis will make it possible to evaluate targets and lead compounds for drug development.
