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Flexible Charged Macromolecules on Mixed Fluid Lipid Membranes: Theory and Monte Carlo Simulations

机译:混合流体脂质膜上的柔性带电大分子:理论和蒙特卡洛模拟

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摘要

Fluid membranes containing charged lipids enhance binding of oppositely charged proteins by mobilizing these lipids into the interaction zone, overcoming the concomitant entropic losses due to lipid segregation and lower conformational freedom upon macromolecule adsorption. We study this energetic-entropic interplay using Monte Carlo simulations and theory. Our model system consists of a flexible cationic polyelectrolyte, interacting, via Debye-Hückel and short-ranged repulsive potentials, with membranes containing neutral lipids, 1% tetravalent, and 10% (or 1%) monovalent anionic lipids. Adsorption onto a fluid membrane is invariably stronger than to an equally charged frozen or uniform membrane. Although monovalent lipids may suffice for binding rigid macromolecules, polyvalent counter-lipids (e.g., phosphatidylinositol 4,5 bisphosphate), whose entropy loss upon localization is negligible, are crucial for binding flexible macromolecules, which lose conformational entropy upon adsorption. Extending Rosenbluth's Monte Carlo scheme we directly simulate polymer adsorption on fluid membranes. Yet, we argue that similar information could be derived from a biased superposition of quenched membrane simulations. Using a simple cell model we account for surface concentration effects, and show that the average adsorption probabilities on annealed and quenched membranes coincide at vanishing surface concentrations. We discuss the relevance of our model to the electrostatic-switch mechanism of, e.g., the myristoylated alanine-rich C kinase substrate protein.
机译:包含带电荷脂质的流体膜通过将这些脂质动员到相互作用区来增强带相反电荷的蛋白质的结合,克服了由于脂质分离和大分子吸附时较低的构象自由所造成的伴随的熵损失。我们使用蒙特卡洛模拟和理论研究这种能量-熵相互作用。我们的模型系统由柔性的阳离子聚电解质组成,该电解质通过Debye-Hückel和短程排斥势与包含中性脂质,1%四价和10%(或1%)单价阴离子脂质的膜相互作用。固定在流体膜上的吸附力总是比等电荷的冷冻或均匀膜强。尽管一价脂质足以结合刚性大分子,但对于结合柔性大分子而言至关重要的多价抗脂质(例如磷脂酰肌醇4,5双磷酸酯)在定位时的熵损失可忽略不计,但对于结合柔性大分子则至关重要,而柔性大分子在吸附时会失去构象熵。扩展Rosenbluth的Monte Carlo方案,我们可以直接模拟聚合物在流体膜上的吸附。但是,我们认为类似的信息可能来自淬火膜模拟的有偏叠加。使用简单的细胞模型,我们可以说明表面浓度的影响,并表明在消失的表面浓度下,退火和淬火膜的平均吸附概率一致。我们讨论了我们的模型与例如富含肉豆蔻基化的富含丙氨酸的C激酶底物蛋白的静电开关机制的相关性。

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