BIOT 177 |
| Recent biochemical and epidemiological studies have shown that the signaling through the epidermal growth factor receptor (EGFR) can be sensitive to various tyrosine kinase inhibitors (TKIs) depending on the receptor's expression level and whether or not the tyrosine kinase domain harbors any somatic mutations. We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics, signal transduction, and inhibition of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our simulations reveal molecular mechanisms for receptor kinase activation and show that the drug sensitizing mutation (L834R) of EGFR signals preferentially to evoke a downstream Akt response and is also preferentially susceptible for its inhibition explaining the hyper-sensitivity of the tyrosine kinase inhibitor erlotinib in cell-lines carrying the mutation. These results are consistent with qualitative/quantitative experimental measurements reported in the literature. We believe that our model driven approach will in the long-term significantly impact the optimization of future small molecule therapeutic inhibition strategies as well as the formulation of drug-resistance models. Y. Liu, J. Purvis, A. Shih, J. Weinstein, N. Agrawal, R. Radhakrishnan, 2007, Annals of Biomedical Engineering, in press; J. Purvis, Y. Liu, V. Ilango, and R. Radhakrishnan, to be submitted to IEE Sys Biol. |
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Emerging Technologies: Systems Biology
8:00 AM-11:00 AM, Wednesday, August 22, 2007 BCEC -- 108, Oral
Division of Biochemical Technology |