This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor 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.
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