Role of Protein Flexibility in Ion Permeation: A Case Study in Gramicidin A

AbstractProteins have a flexible structure, and their atoms exhibit considerable fluctuations under normal operating conditions. However, apart from some enzyme reactions involving ligand binding, our understanding of the role of flexibility in protein function remains mostly incomplete. Here we investigate this question in the realm of membrane proteins that form ion channels. Specifically, we consider ion permeation in the gramicidin A channel, and study how the energetics of ion conduction changes as the channel structure is progressively changed from completely flexible to a fixed one. For each channel structure, the potential of mean force for a permeating potassium ion is determined from molecular dynamics (MD) simulations. Using the same molecular dynamics data for completely flexible gramicidin A, we also calculate the average densities and fluctuations of the peptide atoms and investigate the correlations between these fluctuations and the motion of a permeating ion. Our results show conclusively that peptide flexibility plays an important role in ion permeation in the gramicidin A channel, thus providing another reason—besides the well-known problem with the description of single file pore water—why this channel cannot be modeled using continuum electrostatics with a fixed structure. The new method developed here for studying the role of protein flexibility on its function clarifies the contributions of the fluctuations to energy and entropy, and places limits on the level of detail required in a coarse-grained model

Randomly hyperbranched polymers

We describe a model for the structures of randomly hyperbranched polymers in solution, and find a logarithmic growth of radius with polymer mass. We include segmental overcrowding, which puts an upper limit on the density. The model is tested against simulations, against data on amylopectin, a major component of starch, on glycogen, and on polyglycerols. For samples of synthetic polyglycerol and glycogen, our model holds well for all the available data. The model reveals higher-level scaling structure in glycogen, related to the beta particles seen in electron microscopy

Molecular Structural Differences between Type-2-Diabetic and Healthy Glycogen

Glycogen is a highly branched glucose polymer functioning as a glucose buffer in animals. Multiple-detector size exclusion chromatography and fluorophore-assisted carbohydrate electrophoresis were used to examine the structure of undegraded native liver glycogen (both whole and enzymatically debranched) as a function of molecular size, isolated from the livers of healthy and db/db mice (the latter a type 2 diabetic model). Both the fully branched and debranched levels of glycogen structure showed fundamental differences between glycogen from healthy and db/db mice. Healthy glycogen had a greater population of large particles, with more α particles (tightly linked assemblages of smaller β particles) than glycogen from db/db mice. These structural differences suggest a new understanding of type 2 diabetes

Comment on: “Energetics and Kinetics of Thermal Ionization Models of MALDI” by Richard Knochenmuss. J. Am. Soc. Mass Spectrom. 25, 1521–1527 (2014)

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Solubility of sodium in sodium chloride: A density functional theory molecular dynamics study

We present the first density functional theory (DFT) molecular dynamics (MD) study of metal-molten-salt solutions using the isobaric-isothermal (NpT) ensemble.We study solutions of excess sodium in molten sodium chloride of concentrations ranging from 0 to 11% Na. We use the Widom particle insertion method to calculate the chemical potential of sodium across this concentration range, and find the solubility limit to be between 3 to 6%, in excellent agreement with the experimental solubility limit. We use the same particle insertion method to calculate the standard reduction potential of sodium in molten sodium chloride as 3.9 ± 0.6 V, in good agreement with the experimental value of 3.18 V. We demonstrate the robustness of our DFT-MD particle insertion method, and discuss applications of our method to modeling electrowinning recycling processes of rare earth metals

Interpreting size-exclusion data for highly branched biopolymers by reverse Monte Carlo simulations

Size-exclusion chromatography with multiple detection provides data on the distributions of various properties in a branched polymer sample, for example, distributions of the number, average mass, mean-squared mass, and branching fraction against hydrodynamic volume. A method is developed that provides a basis to use such data for obtaining structural and biosynthetic information on highly branched polymers, such as amylopectin. We generate by simulation a reference distribution of randomly branched polymers from the experimental distribution of debranched chains of the target polymer. We then select from these simulated chains a set with the same number (or other) distribution as the actual polymer sample, using reverse Monte Carlo simulations. Properties of these model polymers are used to interpret the differences with experiment as due to correlations in branching structure. The same methodology can be applied to data from other separation techniques such as field-flow fractionation and high-performance anionic exchange chromatography

The structure of cardiac glycogen in healthy mice

Transmission electron micrographs of glycogen extracted from healthy mouse hearts reveal aggregate structures around 133 nm in diameter. These structures are similar to, but on average somewhat smaller than, the alpha-particles of glycogen found in mammalian liver. Like the larger liver glycogens, these new particles in cardiac tissue appear to be aggregates of beta-particles. Free beta-particles are also present in liver, and are the only type of particle seen in skeletal muscle. They have diameters from 20 to 50 nm. We discuss the number distributions of glycogen particle diameters and the implications for the structure-function relationship of glycogens in these tissues. We point out the possible implications for the study of glycogen storage diseases, and of non-insulin dependent diabetes mellitus. (C) 2012 Elsevier B.V. All rights reserved