MOLECULAR DYNAMICS SIMULATION OF VESICLE FUSION MECHANISMS

囊泡融合机制的分子动力学模拟

• 批准号: 7601433
• 负责人: VIJAY S PANDE
• 金额: $ 0.03万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7601433
• 关键词: Architecture; Biological Models; Computer Retrieval of Information on Scientific Projects Database; Coupled; Data; Funding; Grant; Individual; Infection; Institution; Kinetics; Measurement; Membrane Fusion; Modeling; Physiological; Process; Reaction; Research; Research Personnel; Resolution; Resources; Seeds; Simulate; Source; Staging; Structure; Synapses; Techniques; United States National Institutes of Health; Vesicle; Virus; base; cluster computing; millisecond; molecular dynamics; neurotransmission; novel; particle; simulation; supercomputer

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Membrane fusion is a key stage in cellular import and export processes such as infection by enveloped viruses and synaptic neurotransmission. Because obtaining high-resolution structural and kinetic measurements of fusion intermediates has been challenging experimentally, membrane fusion is a natural target for simulation studies. For small vesicles, we have performed a few long simulations for fusion and then, using these long trajectories as seeds, utilized the power of the Folding @Home distributed computing project to simulate via molecular dynamics the reaction trajectories of 10,000 individual fusion reactions. Using a novel analytic technique based on Markovian State Models, we have combined these trajectories to predict the structures and kinetics of fusion intermediates on a sub-millisecond timescale. We are now applying the same approach to larger and more physiologically relevant fusion simulations. Current simulations calculate the dynamics of >1,000,000 particles over microseconds, multiplied over multiple reaction trajectories. At this scale, it is critical to have a large, tightly coupled supercomputer to perform the initial trajectories. We will then leverage these trajectories using the highly parallel but loosely coupled architecture of Folding @Home to obtain reaction kinetics and intermediates for fusion. We propose to use the PSC Big Ben tightly-coupled supercomputer to compute these long-timescale trajectories. Using these data, we hope to generate more accurate models of the fusion process on a scale consistent with experimental model systems and with physiological vesicles, thus achieving a new understanding of the fusion reaction.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 膜融合是细胞进口和输出过程的关键阶段，例如被包膜病毒和突触神经传递感染。由于融合中间体的高分辨率结构和动力学测量在实验上具有挑战性，因此膜融合是模拟研究的自然靶标。对于小囊泡，我们进行了一些长时间的融合模拟，然后使用这些长轨迹作为种子，利用了折叠@Home分布式计算项目的功能通过分子动力学模拟10,000个单个融合反应的反应轨迹。使用基于马尔可夫状态模型的新型分析技术，我们将这些轨迹结合在一起，以预测亚毫秒级融合中间体的结构和动力学。现在，我们正在将相同的方法应用于更大且更具生理上相关的融合模拟。当前的模拟计算了微秒上> 1,000,000个颗粒的动力学，而乘以多个反应轨迹。在这个规模上，拥有一个大型，紧密耦合的超级计算机以执行初始轨迹至关重要。然后，我们将使用高度平行但松散的折叠式结构来利用这些轨迹，以获得融合的反应动力学和中间体。我们建议使用PSC Big Big紧密耦合的超级计算机来计算这些长时间的轨迹。使用这些数据，我们希望在与实验模型系统和生理囊泡一致的量表上生成更准确的融合过程模型，从而实现对融合反应的新理解。