Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion
Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion
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DOI：
10.1073/pnas.0601597103
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发表时间：
2006-08-08
影响因子：
11.1
通讯作者：
Pande, Vijay S.
中科院分区：
文献类型：
--
作者：
Kasson, Peter M.;Kelley, Nicholas W.;Pande, Vijay S.
脂质膜融合对细胞转运和信号传导过程如组成性分泌、神经递质释放和包膜病毒感染至关重要。在这里，我们介绍了一个强大的计算方法，用于模拟膜融合从一个初始配置，旨在近似激活的融合前组件从神经元和病毒融合，产生的结果的时间尺度和程度的机械细节，以前不可能我们的知识。我们使用的方法，通过构建一个马尔可夫状态模型与大规模的分布式计算融合的长时间尺度模拟，产生的时间尺度上的融合机制的理解以前不可能模拟我们的知识。我们的模拟数据表明，一个分支的融合途径，其中一个共同的茎状中间体可以迅速形成一个融合孔或保持在亚稳态半融合状态，慢慢形成完全融合的囊泡。这个分支的反应途径提供了一个机制解释的两相融合动力学和稳定的半融合的中间体先前观察到的实验。我们的分布式计算和马尔可夫状态模型方法提供了足够的采样来检测罕见的转换，分析反应途径的系统过程，并能够开发定量近似的反应动力学融合。
Lipid membrane fusion is critical to cellular transport and signaling processes such as constitutive secretion, neurotransmitter release, and infection by enveloped viruses. Here, we introduce a powerful computational methodology for simulating membrane fusion from a starting configuration designed to approximate activated prefusion assemblies from neuronal and viral fusion, producing results on a time scale and degree of mechanistic detail not previously possible to our knowledge. We use an approach to the long time scale simulation of fusion by constructing a Markovian state model with large-scale distributed computing, yielding an understanding of fusion mechanisms on time scales previously impossible to simulate to our knowledge. Our simulation data suggest a branched pathway for fusion, in which a common stalk-like intermediate can either rapidly form a fusion pore or remain in a metastable hemifused state that slowly forms fully fused vesicles. This branched reaction pathway provides a mechanistic explanation both for the biphasic fusion kinetics and the stable hemifused intermediates previously observed experimentally. Our distributed computing and Markovian state model approaches provide sufficient sampling to detect rare transitions, a systematic process for analyzing reaction pathways, and the ability to develop quantitative approximations of reaction kinetics for fusion.