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.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 膜融合是细胞输入和输出过程中的关键阶段，例如包膜病毒感染和突触神经传递。由于获得高分辨率的结构和动力学测量的融合中间体一直具有挑战性的实验，膜融合是一个自然的目标模拟研究。对于小囊泡，我们已经进行了一些长的融合模拟，然后使用这些长轨迹作为种子，利用Folding @Home分布式计算项目的力量，通过分子动力学模拟10，000个单独融合反应的反应轨迹。使用一种新的分析技术的基础上马尔可夫状态模型，我们结合这些轨迹预测的结构和动力学的融合中间体在亚毫秒的时间尺度。我们现在正在将相同的方法应用于更大和更生理相关的融合模拟。目前的模拟计算超过1，000，000个粒子在微秒内的动力学，乘以多个反应轨迹。在这种规模下，拥有一台大型、紧密耦合的超级计算机来执行初始轨迹是至关重要的。然后，我们将利用Folding @Home的高度并行但松散耦合的架构来利用这些轨迹，以获得反应动力学和聚变中间体。我们建议使用PSC大本钟紧耦合超级计算机来计算这些长时间尺度的轨迹。利用这些数据，我们希望在与实验模型系统和生理囊泡一致的规模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。