相关实验视频
通过马尔科夫状态模型分析揭示脂质自组的热力学和动力学
Jingwei Weng1, Maohua Yang1, Wenning Wang1
1Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Ministry of Education Key Laboratory of Computational Physical Sciences, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China.
Journal of the American Chemical Society
|December 14, 2020
概括
马尔科夫状态模型分析揭示了二甲基酸胆 (DPPC) 脂质自我组合中的自由能量障碍. 这种计算方法揭示了新的途径和超稳定状态, 进步了我们对材料制造的理解.
科学领域:
- 计算化学和材料科学
- 生物物理和分子建模
- 自组装的热力学和动力学
背景情况:
- 自组合在生物学和材料科学中至关重要,但理解它的热力学和动力学仍然具有挑战性.
- 分子动力学 (MD) 模拟提供原子层次的细节,但与热力学和动力学见解作斗争.
- 之前的研究推测脂质自组的自由能量障碍没有确的证据.
研究的目的:
- 应用马尔科夫状态模型分析以阐明二米托胆 (DPPC) 脂质自组合过程中的自由能量变化.
- 识别和描述DPPC自组装过程中的中间状态和过渡障碍.
- 为了解脂质自我组合提供定量框架,并激发实验设计.
主要方法:
- 广泛的分子动力学 (MD) 模拟超过五百个轨迹.
- 对MD数据应用的马尔科夫状态模型 (MSM) 分析.
- 使用溶剂可访问的表面积和根的平方平均偏差来推导自由能量概况.
主要成果:
- 识别了一个超稳定的交叉圆柱体 (CC) 状态和一个扭曲的双层过渡状态.
- 每个DPPC脂质约为0.02kJ的自由能量屏障.
- 发现了两种新的中相结构和两种以前未报告的到CC状态的组装途径.
- 分析了力-的补偿,强调其在自由能量格局中的作用.
结论:
- 马尔科夫状态模型分析在自组装系统中有效地划分自由能量景观.
- 这项研究证实DPPC脂质自组合中存在自由能量障碍,解决了长达20年的问题.
- 对早期中相和组合途径的新见解提供了对脂质自我组织的更深入的理解.
- 开发的策略提供了一种定量方法来研究自组装,潜在的精炼力场和指导实验.
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