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整合分子动力学产生亚毫秒级动力学和膜融合中间体。

Ensemble molecular dynamics yields submillisecond kinetics and intermediates of membrane fusion.

作者信息

Kasson Peter M, Kelley Nicholas W, Singhal Nina, Vrljic Marija, Brunger Axel T, Pande Vijay S

机构信息

Medical Scientist Training and Biophysics Programs, Department of Computer Science, Stanford Synchrotron Radiation Laboratory, Stanford University, Stanford, CA 94305, USA.

出版信息

Proc Natl Acad Sci U S A. 2006 Aug 8;103(32):11916-21. doi: 10.1073/pnas.0601597103. Epub 2006 Jul 31.

DOI:10.1073/pnas.0601597103
PMID:16880392
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1567673/
Abstract

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.

摘要

脂质膜融合对于细胞运输和信号传导过程至关重要,如组成型分泌、神经递质释放以及包膜病毒感染。在此,我们引入了一种强大的计算方法,用于从一个起始构型模拟膜融合,该构型旨在近似神经元和病毒融合中的活化预融合组装体,在时间尺度和机械细节程度上产生了据我们所知以前无法获得的结果。我们通过使用大规模分布式计算构建马尔可夫状态模型的方法来进行融合的长时间尺度模拟,从而在据我们所知以前无法模拟的时间尺度上理解融合机制。我们的模拟数据表明融合存在一条分支途径,其中一个常见的茎状中间体既可以快速形成融合孔,也可以保持在亚稳态半融合状态,该状态会缓慢形成完全融合的囊泡。这种分支反应途径为双相融合动力学以及先前实验观察到的稳定半融合中间体提供了一种机理解释。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以检测罕见转变、分析反应途径的系统过程以及开发融合反应动力学定量近似的能力。

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