To begin to elucidate the principles of intermolecular dynamics in the crowded environment of cells, employing Brownian dynamics (BD) simulations, we examined possible mechanism(s) responsible for the great reduction in diffusion constants of macromolecules in vivo from that at infinite dilution. In an Escherichia coli cytoplasm model comprised of 15 different macromolecule types at physiological concentrations, BD simulations of molecular-shaped and equivalent sphere representations were performed with a soft repulsive potential. At cellular concentrations, the calculated diffusion constant of GFP is much larger than experiment, with no significant shape dependence. Next, using the equivalent sphere system, hydrodynamic interactions (HI) were considered. Without adjustable parameters, the in vivo experimental GFP diffusion constant was reproduced. Finally, the effects of nonspecific attractive interactions were examined. The reduction in diffusivity is very sensitive to macromolecular radius with the motion of the largest macromolecules dramatically slowed down; this is not seen if HI dominate. In addition, long-lived clusters involving the largest macromolecules form if attractions dominate, whereas HI give rise to significant, size independent intermolecular dynamic correlations. These qualitative differences provide a testable means of differentiating the importance of HI vs. nonspecific attractive interactions on macromolecular motion in cells. Brownian dynamics | correlated motionO ne of the most characteristic features of the interiors of cells is the high total concentration of biological macromolecules. Typically, 20%-40% of the cytoplasmic volume is occupied by proteins, nucleic acids, and other macromolecules (1-3). Under these conditions, although the molar concentration of each protein ranges from nM to μM, the distance between neighboring proteins is comparable to the size of the proteins. Therefore, simulating the crowded intracellular environment is crucial to understanding the nature of living systems.Macromolecular crowding exerts surprisingly large effects on the thermodynamics and kinetics of processes such as macromolecular association, protein stability, and enzyme activity (1, 4, 5). The diffusion and partitioning of macromolecules are highly restricted by intermolecular steric repulsions as well as nonspecific attractive interactions. Consequently, the in vivo and in vitro rates and equilibria of biological reactions can differ by orders of magnitude. While there have been several models of metabolic networks or signaling pathways designed to elucidate the relationship between molecular and cellular behavior (6), effects of macromolecular crowding are at best only partially considered (7).Diffusion is one of the most important physical parameters that describe motions of molecules in a fluid. The diffusion constants of macromolecules in the cytoplasm as well as in membranes have been measured by various techniques including "single-particle tracking" (8), "fluorescence recovery after phot...

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.DOI: http://dx.doi.org/10.7554/eLife.19274.001

Left-right asymmetry in cell shape is converted to a directional twist of the gut epithelial tube.

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc.