Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery: Bridging Experiments and Computations - September 10-14, 2014, Istanbul, Turkey

Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery Session III Abstracts

Regulation of Protein-Protein Binding and Pathway Crosstalk Anna Panchenko . National Institutes of Health, Bethesda, MD, USA.

Phosphorylation offers a dynamic way to regulate protein activity and subcellular localization, which is achieved through reversibility and fast kinetics of posttranslational modifications. Adding or removing a dianionic phosphate group on a protein often changes protein’s structural properties, its stability and dynamics. We estimate the effect of phosphorylation on protein binding and function for different types of complexes from human proteome. We find that phosphorylation sites tend to be located on protein-protein binding interfaces and may orthosterically modulate the strength of interactions. We study the effect of phosphorylation on protein-protein binding in relation to intrinsic disorder and observe the coupling between phosphorylation events and protein-protein binding through disorder-order or order-disorder transitions. Finally we investigate how different phosphorylation patterns may mediate dynamic regulation of cellular processes and may provide the biological cross-talk between different biochemical pathways.

Stochastic Simulations of Cellular Processes: from Single Cells to Colonies

Zaida Luthey-Schulten. University of Illinois at Urbana-Champaign, Urbana, IL, USA

High-performance computing now allows integration of data from structural, single-molecule, and biochemical studies into coherent computational models of cells and cellular processes under in vivo conditions. Here we analyze the stochastic reaction-diffusion dynamics of a genetic switch, ribosome assembly, and metabolic responses of Escherichia coli cells. Using our GPU based Lattice Microbe software, we simulate the dynamics for an entire cell cycle and compare the mRNA/protein distributions to those observed in single molecule experiments. We show how such distributions can be integrated into a flux balance analysis of genome scale models of metabolic networks. The distribution of growth rates calculated for a colony of bacteria are analyzed and correlated to changes in fluxes through the metabolic network for various subpopulations. Finally, reaction-diffusion kinetics of the surrounding medium are coupled with the cellular metabolic networks to demonstrate how small colonies of interacting bacterial cells differentially respond to the competition for resources according to their position in the colony.

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