Samanta, H. | Search bioRxiv

bioRxiv2018

Charge fluctuation effects on the shape of flexible polyampholytes with applications to Intrinsically disordered proteins

Random polyampholytes (PAs) contain positively and negatively charged monomers that are distributed randomly along the polymer chain. The interaction between charges is assumed to be given by the Debye-Huckel potential. We show that the size of the PA is determined by an interplay between electrostatic interactions, giving rise to the polyelectrolyte (PE) effect due to net charge per monomer ({sigma}), and an effective attractive PA interaction due to charge fluctuations,{delta}{sigma} . The interplay between these terms gives rise to non-monotonic dependence of the radius of gyration, Rg on the inverse Debye length,{kappa} when PA effects are important [Formula]. In the opposite limit, Rg decreases monotonically with increasing{kappa} . Simulations of PA chains, using a charged bead-spring model, further corroborates our theoretical predictions. The simulations unambiguously show that conformational heterogeneity manifests itself among sequences that have identical PA parameters. A clear implication is that the phases of PA sequences, and by inference IDPs, cannot be determined using only the bare PA parameters ({sigma} and{delta}{sigma} ).The theory is used to calculate the changes in Rg on N, the number of residues for a set of Intrinsically Disordered Proteins (IDPs). For a certain class of IDPs, with N between 24 to 441, the size grows as Rg ~ N0.6, which agrees with data from Small Angle X-ray Scattering (SAXS) experiments.

biophysics↗

bioRxiv2017

Optimal Information Transfer In Enzymatic Networks: A Field Theoretic Formulation

Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach in order to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus (Phys. Rev. X., 4, 041017 (2014)). We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudo intermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudo intermediate. Surprisingly, in these examples the minimum error computed using simulations that take non-linearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in networks of arbitrary complexity.

biophysics↗