Anomalous versus slowed-down Brownian diffusion in the ligand-binding equilibrium

Measurements of protein motion in living cells and membranes consistently report transient anomalous diffusion (subdiffusion) which converges back to a Brownian motion with reduced diffusion coefficient at long times, after the anomalous diffusion regime. Therefore, slowed-down Brownian motion could be considered the macroscopic limit of transient anomalous diffusion. On the other hand, membranes are also heterogeneous media in which Brownian motion may be locally slowed-down due to variations in lipid composition. Here, we investigate whether both situations lead to a similar behavior for the reversible ligand-binding reaction in 2d. We compare the (long-time) equilibrium properties obtained with transient anomalous diffusion due to obstacle hindrance or power-law distributed residence times (continuous-time random walks) to those obtained with space-dependent slowed-down Brownian motion. Using theoretical arguments and Monte-Carlo simulations, we show that those three scenarios have distinctive effects on the apparent affinity of the reaction. While continuous-time random walks decrease the apparent affinity of the reaction, locally slowed-down Brownian motion and local hinderance by obstacles both improve it. However, only in the case of slowed-down Brownian motion, the affinity is maximal when the slowdown is restricted to a subregion of the available space. Hence, even at long times (equilibrium), these processes are different and exhibit irreconcilable behaviors when the area fraction of reduced mobility changes.Comment: Biophysical Journal (2013

Generic principles of active transport

Nonequilibrium collective motion is ubiquitous in nature and often results in a rich collection of intringuing phenomena, such as the formation of shocks or patterns, subdiffusive kinetics, traffic jams, and nonequilibrium phase transitions. These stochastic many-body features characterize transport processes in biology, soft condensed matter and, possibly, also in nanoscience. Inspired by these applications, a wide class of lattice-gas models has recently been considered. Building on the celebrated {\it totally asymmetric simple exclusion process} (TASEP) and a generalization accounting for the exchanges with a reservoir, we discuss the qualitative and quantitative nonequilibrium properties of these model systems. We specifically analyze the case of a dimeric lattice gas, the transport in the presence of pointwise disorder and along coupled tracks.Comment: 21 pages, 10 figures. Pedagogical paper based on a lecture delivered at the conference on "Stochastic models in biological sciences" (May 29 - June 2, 2006 in Warsaw). For the Banach Center Publication

Anomalous Diffusion and Non-classical Reaction Kinetics in Crowded Fluids

This thesis investigates the underlying mechanism and the effects of anomalous diffusion in crowded fluids by means of computer simulations. In order to elucidate the mechanism behind crowding-induced subdiffusion we discuss the average shape of tracer trajectories as a potential criterion that allows to reliably discriminate between frequently proposed models. Our simulations show that measurement errors inherent to single particle tracking generally impair the determination of the underlying random process from experimental data. We propose a particle-based model for the crowded cytoplasm that incorporates soft-core repulsion and weak attraction between globular proteins of various sizes. Under these prerequisites simulations reveal transient subdiffusion of proteins. On experimental time scales, however, diffusion is normal indicating that realistic, microscopic models of crowded fluids require further detail of the relevant interactions. In the second part of this thesis, the impact of subdiffusion on biochemical reactions is studied via mesoscopic, stochastic simulations. Due to their compact trajectories subdiffusive reactants get increasingly segregated over time. This results in anomalous kinetics that differs strongly from classical theories. Moreover, for a two-step reaction scheme relying on an intermediate dissociation-association event, subdiffusion can substantially improve the overall productivity because spatio-temporal correlations are exploited with high efficiency

Modeling of solvent flow effects in enzyme catalysis under physiological conditions

A stochastic model for the dynamics of enzymatic catalysis in explicit, effective solvents under physiological conditions is presented. Analytically-computed first passage time densities of a diffusing particle in a spherical shell with absorbing boundaries are combined with densities obtained from explicit simulation to obtain the overall probability density for the total reaction cycle time of the enzymatic system. The method is used to investigate the catalytic transfer of a phosphoryl group in a phosphoglycerate kinase-ADP-bis phosphoglycerate system, one of the steps of glycolysis. The direct simulation of the enzyme-substrate binding and reaction is carried out using an elastic network model for the protein, and the solvent motions are described by multiparticle collision dynamics, which incorporates hydrodynamic flow effects. Systems where solvent-enzyme coupling occurs through explicit intermolecular interactions, as well as systems where this coupling is taken into account by including the protein and substrate in the multiparticle collision step, are investigated and compared with simulations where hydrodynamic coupling is absent. It is demonstrated that the flow of solvent particles around the enzyme facilitates the large-scale hinge motion of the enzyme with bound substrates, and has a significant impact on the shape of the probability densities and average time scales of substrate binding for substrates near the enzyme, the closure of the enzyme after binding, and the overall time of completion of the cycle.Comment: 15 pages in double column forma