189 research outputs found

    Notes on the Treatment of Charged Particles for Studying Cyclotide/Membrane Interactions with Dissipative Particle Dynamics

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    Different charge treatment approaches are examined for cyclotide-induced plasma membrane disruption by lipid extraction studied with dissipative particle dynamics. A pure Coulomb approach with truncated forces tuned to avoid individual strong ion pairing still reveals hidden statistical pairing effects that may lead to artificial membrane stabilization or distortion of cyclotide activity depending on the cyclotide’s charge state. While qualitative behavior is not affected in an apparent manner, more sensitive quantitative evaluations can be systematically biased. The findings suggest a charge smearing of point charges by an adequate charge distribution. For large mesoscopic simulation boxes, approximations for the Ewald sum to account for mirror charges due to periodic boundary conditions are of negligible influence

    Molecular Dynamics Studies of PEGylated Antimicrobial Peptides with Lipid Bilayers

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    Atomistic Monte Carlo simulation of lipid membranes

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    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol

    Atomistic Monte Carlo simulation of lipid membranes

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    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol

    Surface topography of membrane domains

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    金沢大学理工研究域数物科学系Elucidating origin, composition, size, and lifetime of microdomains in biological membranes remains a major issue for the understanding of cell biology. For lipid domains, the lack of a direct access to the behaviour of samples at the mesoscopic scale has constituted for long a major obstacle to their characterization, even in simple model systems made of immiscible binary mixtures. By its capacity to image soft surfaces with a resolution that extends from the molecular to the microscopic level, in air as well as under liquid, atomic force microscopy (AFM) has filled this gap and has become an inescapable tool in the study of the surface topography of model membrane domains, the first essential step for the understanding of biomembranes organization. In this review we mainly focus on the type of information on lipid microdomains in model systems that only AFM can provide. We will also examine how AFM can contribute to understand data acquired by a variety of other techniques and present recent developments which might open new avenues in model and biomembrane AFM applications. © 2009 Elsevier B.V. All rights reserved

    11th German Conference on Chemoinformatics (GCC 2015) : Fulda, Germany. 8-10 November 2015.

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    Computational Modeling of Realistic Cell Membranes

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    Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead

    Network of lipid interconnections at the interfaces of galactolipid and phospholipid bilayers

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    Interactions among lipid head groups at the bilayer/water interface do, to a large extent, determine membrane properties. In this study graph theory is employed to objectively describe and compare the pattern of the interactions at the interfaces of computer models of 128- and 512-lipid monogalactolipid (MGDG) and phosphatidylcholine (DOPC) bilayers. Both MGDG and DOPC have polar head groups but of different chemical structures so at the bilayer interfaces they participate in different types of interaction. Nevertheless, at both interfaces these interactions and the lipid molecules they link make networks. In graph theory, a network of interconnected objects (nodes) is described by well-defined quantities which define its topology and can be used to assess inner properties of the network, its strength and density, etc. In this study, several topological properties of the networks in the DOPC and MGDG bilayers are determined. A comparison of these properties indicates that the topologies of both networks differ significantly but are stable during the simulation time. The networks in the MGDG bilayers are more extended, branched, stable, and stronger than those in the DOPC bilayers. This is consistent with the smaller surface area per lipid and higher rigidity of the MGDG than the DOPC bilayers as well as the tendency of MGDG to form an inverse hexagonal phase in water. The scale of the systems is an important factor when assessing the properties of the network; the system scaling is more evident in the DOPC bilayers where several quantities increase directly proportional to the increasing size of the system than in the MGDG bilayers where this is rarely the case

    Molecular Simulations of Protein-Induced Membrane Remodeling

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    Membranes organize much of the cell and host a great deal of molecular machinery required to integrate signals from the outside, regulate the surrounding matrix, change shape, move, and grow. Understanding how a dense forest of proteins, sugars, and biomarkers modulates the shape of the cell is necessary to produce more detailed, accurate predictions of cell behavior, particularly in the studies of cell signaling processes that lead to oncogenesis. In this dissertation, I will present a series of molecular models which, when combined with continuum models and both in vitro and in vivo experiments, describe the molecular basis for membrane morphology changes. In particular, we investigate the mechanisms by which proteins assemble on a bilayer undergoing thermal fluctuations. This work serves to quantify and explain a series of biophysical experiments in molecular detail, and contributes to the development of multiscale models for predicting cell fate
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