Physical model for the gating mechanism of ionic channels

We propose a physical model for the gating mechanism of ionic channels. First, we investigate the fluctuation-mediated interactions between two proteins imbedded in a cellular membrane and find that the interaction depends on their orientational configuration as well as the distance between them. The orientational dependence of interactions arises from the fact that the noncircular cross-sectional shapes of individual proteins constrain fluctuations of the membrane differently according to their orientational configuration. Then, we apply these interactions to ionic channels composed of four, five, and six proteins. As the gating stimulus creates the changes in the structural shape of proteins composing ionic channels, the orientational configuration of the ionic channels changes due to the free energy minimization, and ionic channels are open or closed according to the conformation thereof.open3

Atoms to phenotypes: Molecular design principles of cellular energy metabolism

We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore’s structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells

Molecular Dynamics Studies of Lipid Bilayers

Introduction Presently Molecular Dynamics (MD) simulations are feasible for systems comprising tens of thousands of atoms and can extend over time scales of a few nanoseconds. While it is clear that many-if not most- of the biologically relevant questions concern much larger systems and much longer time scales and hence are beyond the `brute force' application of MD, there are also a number of relevant questions within reach of the method. The structure and dynamics of bilayer membranes in their liquid-crystalline state belongs to the latter class of problems. The cooperativity is such that a subsystem of less than 10,000 atoms suffices to include all relevant interactions, provided the boundaries of the system are described properly. The time scale of the motion of phospholipids in membranes is such that sufficient averaging occurs on the attainable time scale of nanoseconds. This still excludes the proper study of phase separation in mixed lipid membranes, or even of simpl

Molecular Dynamics Simulation of the Kinetics of Spontaneous Micelle Formation

Using an atom based force field, molecular dynamics (MD) simulations of 54 dodecylphosphocholine (DPC) surfactant molecules in water at two different concentrations above the critical micelle concentration have been performed. Starting from a random distribution of surfactants, we observed the spontaneous aggregation of the surfactants into a single micelle. At the higher DPC concentration (0.46 M) the surfactants aggregated into a worm-like micelle within 1 ns, whereas at lower concentration (0.12 M) they aggregated on a slower time scale (~12 ns) into a spherical micelle. The difference in the final aggregate is a direct consequence of the system achieving the lowest free energy configuration for a given quantity of surfactant within the periodic boundary conditions. The simulation at low surfactant concentration was repeated three times in order to obtain statistics on the rate of aggregation. It was found that the aggregation occurs at a (virtually) constant rate with a rate constant of k = 1 × 10-4 ps-1. This is an unexpected result. On the basis of Monte Carlo simulations of a stochastic description of the system, using diffusion rates and cluster radii as determined by separate MD simulations of single DPC clusters, a lower rate constant which diminishes in the course of the aggregation process had been predicted. Neglect of hydrodynamic interactions, of long-range hydrophobic interactions, or of spatial correlations in the stochastic approach might account for the descrepancies with the more accurate MD simulations.