Using a recently developed multiscale simulation methodology, we describe the equilibrium behaviour of bilayer membranes under the influence of curvature-inducing proteins using a linearized elastic free energy model. In particular, we describe how the cooperativity associated with a multitude of protein-membrane interactions and protein diffusion on a membrane-mediated energy landscape elicits emergent behaviour in the membrane phase. Based on our model simulations, we predict that, depending on the density of membrane-bound proteins and the degree to which a single protein molecule can induce intrinsic mean curvature in the membrane, a range of membrane phase behaviour can be observed including two different modes of vesicle-bud nucleation and repressed membrane undulations. A state diagram as a function of experimentally tunable parameters to classify the underlying states is proposed.

Abstract-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 dimermediated 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.

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Poster abstracts 81 regulated during adverse drug reactions. Such information provides us with a more detailed understanding of the molecular mechanisms underlying toxic effects. Additionally, microarray technology can be used to identify gene expression profiles for new therapeutic compounds, thus providing an early screening method for potential toxic effects. An important step in using microarray analysis in toxicity screening is to construct a library of genes that are regulated positively or negatively during hepatotoxicity, as these genes may not be represented in libraries prepared from normal tissue. In order to facilitate this, we have treated rats with hepatotoxins representing diverse structural and therapeutic classes. These compounds induce a variety of hepatotoxic responses including peroxisomal proliferation, hepatic necrosis and apoptosis, cholestasis, DNA damage, protein synthesis inhibition, oxidative stress, mitochondrial damage, P-450 induction and phospholipidosis. The livers were harvested from the treated rats and mRNA was isolated. The mRNA was pooled and gene expression analysis of treated versus untreated rats was assayed using microarray analysis. The data gathered from microarray and sequence analysis allows us to identify signature sets of genes regulated during toxicity. These gene responses are then used to identify mechanisms of toxicity. Knowledge of specific toxicologic pathways can help determine potential human liabilities, and the identification of signature gene sets can be used to evaluate drug candidates for potential adverse effects. In a follow-up case study, using microarrays, we evaluated changes in gene expression in rat liver associated with hypertrophy, hyperplasia and single cell necrosis (apoptosis) following administration of a drug candidate.