We present a general-purpose model for biomolecular simulations at the molecular level that incorporates stochasticity, spatial dependence, and volume exclusion, using diffusing and reacting particles with physical dimensions. To validate the model, we first established the formal relationship between the microscopic model parameters (timestep, move length, and reaction probabilities) and the macroscopic coefficients for diffusion and reaction rate. We then compared simulation results with Smoluchowski theory for diffusion-limited irreversible reactions and the best available approximation for diffusion-influenced reversible reactions. To simulate the volumetric effects of a crowded intracellular environment, we created a virtual cytoplasm composed of a heterogeneous population of particles diffusing at rates appropriate to their size. The particle-size distribution was estimated from the relative abundance, mass, and stoichiometries of protein complexes using an experimentally derived proteome catalog from Escherichia coli K12. Simulated diffusion constants exhibited anomalous behavior as a function of time and crowding. Although significant, the volumetric impact of crowding on diffusion cannot fully account for retarded protein mobility in vivo, suggesting that other biophysical factors are at play. The simulated effect of crowding on barnase-barstar dimerization, an experimentally characterized example of a bimolecular association reaction, reveals a biphasic time course, indicating that crowding exerts different effects over different timescales. These observations illustrate that quantitative realism in biosimulation will depend to some extent on mesoscale phenomena that are not currently well understood.

We study in detail a recently proposed simple discrete model for evolution on smooth landscapes. An asymptotic solution of this model for long times is constructed. We find that the dynamics of the population are governed by correlation functions that although being formally down by powers of $N$ (the population size) nonetheless control the evolution process after a very short transient. The long-time behavior can be found analytically since only one of these higher-order correlators (the two-point function) is relevant. We compare and contrast the exact findings derived herein with a previously proposed phenomenological treatment employing mean field theory supplemented with a cutoff at small population density. Finally, we relate our results to the recently studied case of mutation on a totally flat landscape.Comment: Revtex, 15 pages, + 4 embedded PS figure

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We study a recently proposed mean-field theory relevant for diffusion-limited growth at finite undercooling. This theory exhibits a morphology transition from convex patterns, typical of the densebranching morphology envelope, to concave ones, typical of the dendritic morphology envelope. This transition occurs as the undercooling is lowered at fixed anisotropy, but does not involve any discontinuous behavior of growth velocity.

A high-performance liquid chromatographic separation coupled to diode array absorbance and positive mode electrospraymass spectrometric detection has been developed for the analysis of ginsenosides, malonyl ginsenosides, and hydrolyzed ginsenosides in extracts of Asian ginseng (Panax ginseng) and American ginseng (P. quinquefolius). The method is capable of separating, identifying, and quantifying the predominant ginsenosides found in heated alcoholic extracts of Asian and American ginseng roots routinely sold as nutraceuticals. It also separates and identifies the malonyl ginsenosides often found in cold alcoholic extracts of ginseng root and has the potential to quantify these compounds if pure standards are available. Furthermore, it can separate and identify ginsenoside hydrolysis products such as those readily produced in situations mimicking gastric situations, including those used for dissolution studies (i.e., 0.1 N HCl, 37C).