对可离子化脂质质子化引起的膜破坏的硅学见解

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Zhen Zhao, Hao Zhang, Xiaoyan Zhuang, Lijuan Yan, Guangyong Li, Jun Li, Hui Yan
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引用次数: 0

摘要

脂质纳米颗粒(LNPs)是一种新型的药物传递载体,在核酸药物传递中发挥保护作用。LNPs由各种有机材料组成,这些有机材料承担着相应的任务。在这些成分中,由于脂质纳米颗粒与内体膜磷脂之间的静电相互作用,暴露于内体的酸性pH环境后,可电离脂质会发生局部脂质积累,这有助于膜融合破坏,内体逃逸和货物释放。然而,这些推断在分子水平上缺乏直观的证据,因此我们进行计算模拟以提供分子和细胞生物学事件的微观视图。在这项工作中,我们进行了分子动力学(MD)模拟,以研究电离脂质质子化诱导膜破坏的微观机制。通过模拟内体膜对可电离脂质的摄取过程,得到了含有不同浓度可电离脂质的模型。模拟结果表明,质子化的可电离脂质聚集在内体膜的一侧。通过分子间相互作用的分析,发现这种积累是由于质子化的可电离脂质的头基团与膜脂质的强结合所致。而未质子化的可电离脂质则分散在双分子层的两侧,起到稳定纳米颗粒的作用。可电离脂质的积累对脂质顺序参数和模拟双分子层的厚度产生持续影响,这可能是导致内体膜破裂的原因。方法采用分子动力学模拟和GROMOS 54A7联合原子力场研究可电离脂类的被动扩散过程。使用GROMACS 2019软件进行MD模拟,重点研究了系统在可电离脂质摄取过程中能量和分子分布的变化。分析了工艺结束时系统配置的SDC、厚度和能量等特性。使用VMD将这些模拟配置可视化。采用GridMAT-MD软件包对膜的厚度进行分析。利用GROMACS包中的工具分析了密度分布曲线和能量等其他特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In silico insights into the membrane disruption induced by the protonation of ionizable lipids

Context

Lipid nanoparticles (LNPs) are a novel type of drug delivery carrier, which play a protective role in nucleic acid drug delivery. LNPs are composed of various organic materials and these compositions assume corresponding tasks. Among these components, ionizable lipids undergo localized accumulation of lipids after exposure to the acidic pH environment of endosomes due to electrostatic interactions between lipid nanoparticles and phospholipids in endosomal membranes, which contributes to membrane fusion-disruption, endosomal escape, and cargo release. However, these extrapolations lack intuitive evidence at the molecular level, so we perform computational simulations to provide a microscopic view of molecular and cellular biological events. In this work, we performed molecular dynamics (MD) simulations to study the microscopic mechanism of membrane disruption induced by the protonation of ionizable lipids. Models containing different concentrations of ionizable lipids were obtained by simulating the uptake process of ionizable lipids by the endosomal membrane. The simulated results showed that the protonated ionizable lipids accumulated on one side of the endosomal membrane. Through the analysis of intermolecular interactions, it was found that the accumulation was due to the strong association of the head groups of the protonated ionizable lipids with the membrane lipids. Whereas the unprotonated ionizable lipids were dispersed on both sides of the bilayer, which served to stabilize the nanoparticles. The accumulation of ionizable lipids caused a sustained effect on lipid order parameters and the thickness of the simulated bilayer, which may be responsible for endosomal membrane rupture.

Methods

In this study, we employed MD simulations and used the GROMOS 54A7 united-atom force field to investigate the passive diffusion process of ionizable lipids. MD simulations were performed using the GROMACS 2019 software, focusing on the changes in the energy and molecular distribution of the system during the uptake process of ionizable lipids. Characteristics such as SDC, thickness, and energy of the system configuration at the end of the process are also analyzed. These configurations of the simulations were visualized using VMD. The GridMAT-MD package was adopted to analyze the thickness of the membrane. The other characters such as density distribution profiles and energies were analyzed using the tools within the GROMACS package.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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