2 research outputs found

    Atomistic Simulations of Bicelle Mixtures

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    AbstractMixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C14 tails) and dihexanoylphosphatidylcholine (DHPC, di-C6 tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironments and the stabilization of the bilayer edge by DHPC. To approach equilibrium partitioning of lipids on an achievable simulation timescale, configuration-bias Monte Carlo mutation moves were used to allow individual lipids to change tail length within a semigrand-canonical ensemble. Since acceptance probabilities for direct transitions between DMPC and DHPC were negligible, a third component with intermediate tail length (didecanoylphosphatidylcholine, di-C10 tails) was included at a low concentration to serve as an intermediate for transitions between DMPC and DHPC. Strong enrichment of DHPC is seen at ribbon and pore edges, with an excess linear density of ∼3 nm−1. The simulation model yields estimates for the onset of edge stability with increasing bilayer DHPC content between 5% and 15% DHPC at 300 K and between 7% and 17% DHPC at 323 K, higher than experimental estimates. Local structure and composition at points of close contact between pores suggest a possible mechanism for effective attractions between pores, providing a rationalization for the tendency of bicelle mixtures to aggregate into perforated vesicles and perforated sheets

    Improving Simulations of Aqueous Systems through Experimental Bias

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    In order to enhance the ab initio molecular dynamics treatment of aqueous systems, the Boltzmann inversion directed simulation method was developed that derives a corrective bias to the system pairwise potential using experimental data. The bias acts as an empirical correction that enables routine-level simulation of density functional theory water to achieve comparable liquid structure to experiment at ambient temperature without significantly increasing computational cost
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