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Center for Nonlinear Studies |
Systems biology is likely to have a great impact on the biological sciences in the future. For example, whole genome sequencing, DNA microarrays and proteomics are providing information that can be used to reconstruct cellular networks. However, in order to fully exploit these data, we must develop mathematical, computational and experimental methods to interpret and predict the behavior of cellular networks. In this talk, I will describe our computational and high throughput experimental techniques for elucidating integrated protein function. Namely, we have been studying ErbB receptors, which are gysregulated in a high proportion of cancers and a critical target for anti-cancer drugs. Despite a plethora of biochemical studies and recent single particle tracking experiments, the early molecular mechanisms involving ligand binding and dimerization are not well understood. Herein, we describe a spatially distributed Monte Carlo based simulation framework to enable the simulation of in vivo receptor diffusion and dimerization. Our simulation results are in agreement with the data from single particle tracking and biochemical experiments on ErbB receptors. Additionally, I will describe a strategy we have developed to analyze the impact of single nucleotide mutations on protein function and the global effects on cellular function. Our method utilizes a combination of yeast functional complementation, growth competition of mutant pools and polyacrylamide gel immobilized PCR. Overall, these results show that high-throughput assays can be developed to study human protein function. Overall, we show that simulation high throughput experiments can be used to gain a mechanistic understanding of cellular protein function which may be translated into improved medical treatments in the future.