A model for the lipid pretransition: Coupling of ripple formation with the chain-melting transition

A model for the lipid pretransition: Coupling of ripple formation with the chain-melting transition
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DOI:
10.1016/s0006-3495(00)76673-2
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发表时间:
2000-03-01
影响因子:
3.4
通讯作者:
Heimburg, T
Heimburg, T
中科院分区:
生物学3区
文献类型:
--
作者:
Heimburg, T

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在热致链熔化转变之下,脂质膜c(P)迹线显示低焓的转变,称为脂质预转变。它与周期性膜波纹的形成有关。在文献中,这两个转变通常被视为独立的事件。在这里,我们提出了一个模型,该模型基于这样的假设:预转变和主转变都是由相同的物理效应(即链熔化)引起的。分裂成两个峰值的熔化过程中发现的结构变化和链熔化事件的耦合的后果。在此基础上,我们进行了Monte Carlo模拟使用两个耦合单层晶格。在此计算中,波纹被认为是流体脂质分子的一维缺陷。由于脂质在熔化时改变其面积约24%,因此线缺陷是三角形晶格中唯一可能的拓扑缺陷。在一个单层上形成流体线缺陷导致膜的局部弯曲。几何约束导致凝胶和流体域的周期性图案的形成。这个模型,第一次,能够预测热容量分布,这是可比的实验c(P)的痕迹,我们使用量热法获得。这些基本假设与大量的实验观测结果是一致的。
Below the thermotropic chain-melting transition, lipid membrane c(P) traces display a transition of low enthalpy called the lipid pretransition. It is linked to the formation of periodic membrane ripples. In the literature, these two transitions are usually regarded as independent events. Here, we present a model that is based on the assumption that both pretransition and main transition are caused by the same physical effect, namely chain melting. The splitting of the melting process into two peaks is found to be a consequence of the coupling of structural changes and chain-melting events. On the basis of this concept, we performed Monte Carlo simulations using two coupled monolayer lattices. In this calculation, ripples are considered to be one-dimensional defects of fluid lipid molecules. Because lipids change their area by similar to 24% upon melting, line defects are the only ones that are topologically possible in a triangular lattice. The formation of a fluid line defect on one monolayer leads to a local bending of the membrane. Geometric constraints result in the formation of periodic patterns of gel and fluid domains. This model, for the first time, is able to predict heat capacity profiles, which are comparable to the experimental c(P) traces that we obtained using calorimetry. The basic assumptions are in agreement with a large number of experimental observations.