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 of the Erb family receptors, specifically the
epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the
prior modeling of EGF-mediated
signal transduction by considering specific EGFR
tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and
phosphorylation of different
C-terminal peptide tyrosines on the RTK
tail. 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 molecular dynamics simulations show that the
drug sensitizing
mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for
wildtype vs.
mutant receptors) in inhibitor binding as well as preferential enhancement of
phosphorylation of particular
substrate tyrosines over others. We find that in comparison to the
wildtype system, the L834R
mutant RTK preferentially binds the inhibitor
erlotinib, as well as preferentially
phosphorylates the
substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential
activation of the
Akt signaling pathway in comparison to the Erk
signaling pathway for cells with normal EGFR expression. For cells with EGFR
over expression, the
mutant over activates both Erk and
Akt pathways, in comparison to
wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (
mutant)
cell lines are shaped differently in relationship to native
cell lines.
