Computation of restoration of ligand response in the random kinetics of a prostate cancer cell signaling pathway

Mutation and/or dysfunction of signaling proteins in the mitogen activated protein kinase (MAPK) signal transduction pathway are frequently observed in various kinds of human cancer. Consistent with this fact, in the present study, we experimentally observe that the epidermal growth factor (EGF) induced activation profile of MAP kinase signaling is not straightforward dose-dependent in the PC3 prostate cancer cells. To find out what parameters and reactions in the pathway are involved in this departure from the normal dose-dependency, a model-based pathway analysis is performed. The pathway is mathematically modeled with 28 rate equations yielding those many ordinary differential equations (ODE) with kinetic rate constants that have been reported to take random values in the existing literature. This has led to us treating the ODE model of the pathways kinetics as a random differential equations (RDE) system in which the parameters are random variables. We show that our RDE model captures the uncertainty in the kinetic rate constants as seen in the behavior of the experimental data and more importantly, upon simulation, exhibits the abnormal EGF dose-dependency of the activation profile of MAP kinase signaling in PC3 prostate cancer cells. The most likely set of values of the kinetic rate constants obtained from fitting the RDE model into the experimental data is then used in a direct transcription based dynamic optimization method for computing the changes needed in these kinetic rate constant values for the restoration of the normal EGF dose response. The last computation identifies the parameters, i.e., the kinetic rate constants in the RDE model, that are the most sensitive to the change in the EGF dose response behavior in the PC3 prostate cancer cells. The reactions in which these most sensitive parameters participate emerge as candidate drug targets on the signaling pathway. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

The orientational relaxation of bipolar active regions

In the mean, bipolar active regions are oriented nearly toroidally, according to Hale's polarity law, with a latitude-dependent tilt known as Joy's Law. The tilt angles of individual active regions deviate from this mean behavior and change over time. It has been found that on average the change is toward the mean angle at a rate characteristic of 4.37 days (Howard, 1996). We show that this orientational relaxation is consistent with the standard model of flux tube emergence from a deep dynamo layer. Under this scenario Joy's law results from the Coriolis effect on the rising flux tube (D'Silva and Choudhuri, 1993), and departures from it result from turbulent buffeting of the tubes (Longcope and Fisher, 1996). We show that relaxation toward Joy's angle occurs because the turbulent perturbations relax on shorter time scales than the perturbations from the Coriolis force. The turbulent perturbations relax more rapidly because they are localized to the topmost portion of the convection zone while the Coriolis perturbations are more widely distributed. If a fully-developed active region remains connected to the strong toroidal magnetic field at the base of the convection zone, its tilt will eventually disappear, leaving it aligned perfectly toroidally. On the other hand, if the flux becomes disconnected from the toroidal field the bipole will assume a tilt indicative of the location of disconnection. We compare models which are connected and disconnected from the toroidal field. Only those disconnected at points very deep in the convection zone a-re consistent with observed time scale of orientational relaxation.

Physically consistent simulation of mesoscale chemical kinetics: The non-negative FIS-alpha method

Biochemical pathways involving chemical kinetics in medium concentrations (i.e., at mesoscale) of the reacting molecules can be approximated as chemical Langevin equations (CLE) systems. We address the physically consistent non-negative simulation of the CLE sample paths as well as the issue of non-Lipschitz diffusion coefficients when a species approaches depletion and any stiffness due to faster reactions. The non-negative Fully Implicit Stochastic alpha (FIS alpha) method in which stopped reaction channels due to depleted reactants are deleted until a reactant concentration rises again, for non-negativity preservation and in which a positive definite Jacobian is maintained to deal with possible stiffness, is proposed and analysed. The method is illustrated with the computation of active Protein Kinase C response in the Protein Kinase C pathway. (C) 2011 Elsevier Inc. All rights reserved.