Modeling SNARE-Mediated Membrane Fusion

项目总结 当膜封闭时，许多基本过程依靠胞吐作用来分泌生物活性分子。 含有神经递质(NTS)、激素或其他分子的囊泡与质膜(PM)融合 并通过融合毛孔释放其内容物。神经传递依赖于神经元突触释放的NT， 当多组分的机器感觉到由动作电位触发的钙离子内流并融合小突触时 在亚毫秒级的时间尺度上，带有质膜的小泡，将NTS释放到突触裂隙中 突触后反应。其他受调节的胞吐作用较慢，例如神经内分泌释放激素。 当刺激大而致密的核心小泡在几秒钟或更长时间后释放内容物时，细胞。 在所有情况下，膜融合步骤由SNARE蛋白完成，当囊泡相关的VAMP (v-SNARE)和两个PM相关的T-SNARE Synaxin和SNAP 25拉链组成一个三元复合体，拉动 这些膜结合在一起，然后融合在一起。然而，膜融合的机制尚不清楚。其他 机械中的组件阻断(“夹子”)陷阱介导的融合，直到“钙！”信号释放夹子。 Synaptopagmin(SYT)是用于同步释放的Ca！“传感器，但钳子和细胞的分子同一性 未建立CA！“触发的解锁机制。SNARE蛋白和其他NT释放的突变 机械部件与神经发育和神经退行性疾病有关，以及 2型糖尿病患者β细胞胰岛素分泌减少与融合孔扩张受损有关。 这项研究的目的是用数学模型来建立调节膜的机制。 融合和调节囊泡及其孔的机制，以控制融合后释放的内容物。 从上一个资助期开始，我们对SNARE介导的分子动力学(MD)进行了模拟 膜融合和NT释放机械结合核心圈套和SYT组件。这个 模拟使用了足够粗粒度(CG)的表示来实现计算要求 融合和释放的毫秒生理时间尺度。目标1是促进圈套介导的融合 使用更逼真的陷阱进行模拟，并使用机器学习对通向膜的路径进行分类 融合是融合小泡大小和其他关键变量的函数。变异的陷阱将被模拟 并与合作者的实验进行了比较。目标2是使用连续统数学建模来建立 融合囊泡-PM复合体及其融合孔的结构、能学和演化及其机制 SNARE和SYT介导的毛孔扩张。目标3是推进NT释放机构的MD模拟 通过引入膜的分子显式表示，并通过加入额外的成分 随着它们的相互作用成为试验性的特征，朝着“重组”的长期目标前进 硅胶机械。模拟将测试假想的Ca！“触发的解锁方案，并将在 SNARE和SYT组件的突变将由我们的合作者在实验中实现。

PROJECT SUMMARY Many basic processes rely on secretion of bioactive molecules by exocytosis, when membrane-enclosed vesicles containing neurotransmitters (NTs), hormones or other molecules fuse with the plasma membrane (PM) and release their contents through fusion pores. Neurotransmission relies on NT release at neuronal synapses, when a multicomponent machinery senses Ca!"influx triggered by an action potential and fuses small synaptic vesicles with the plasma membrane on sub-millisecond timescales, releasing NTs into the synaptic cleft to elicit a post-synaptic response. Other regulated exocytosis is slower, such as hormone release from neuroendocrine cells when a stimulus provokes large dense core vesicles to release contents after seconds or longer. In all cases, the membrane fusion step is accomplished by the SNARE proteins, when vesicle-associated VAMP (the v-SNARE) and two PM-associated t-SNAREs syntaxin and SNAP 25 zipper into a ternary complex, pulling the membranes together and fusing them. However, the mechanism of membrane fusion remains unclear. Other components in the machinery block (“clamp”) SNARE-mediated fusion, until the Ca!"signal releases the clamp. Synaptotagmin (Syt) is the Ca!"sensor for synchronous release, but the molecular identity of the clamp and the Ca!"-triggered unclamping mechanism are not established. Mutations in SNARE proteins and other NT release machinery components are associated with neurodevelopmental and neurodegenerative disorders, and impaired fusion pore dilation is associated with reduced insulin secretion by β-cells of type-2 diabetics. The proposed research aims to use mathematical modeling to establish the mechanisms of regulated membrane fusion and the mechanisms that regulate the vesicle and its pore for controlled contents release following fusion. From the previous funding period, we have working molecular dynamics (MD) simulations of SNARE-mediated membrane fusion and of the NT release machinery incorporating the core SNARE and Syt components. The simulations used sufficiently coarse-grained (CG) representations to achieve the computationally demanding millisecond physiological timescales of fusion and release. Aim 1 is to advance the SNARE-mediated fusion simulations with more realistic SNAREs, and to use machine learning to catalogue the pathways to membrane fusion as a function of the size of the fusing vesicles and other key variables. Mutated SNAREs will be simulated and compared to experiments by collaborators. Aim 2 is to use continuum mathematical modeling to establish the structure, energetics and evolution of the fused vesicle-PM complex and its fusion pore, and the mechanisms of SNARE- and Syt-mediated pore dilation. Aim 3 is to advance the MD simulations of the NT release machinery by introducing molecularly explicit representation of the membranes, and by incorporating additional components as their interactions become experimentally characterized, toward a long-term goal of “reconstituting” the machinery in silico. Simulations will test hypothesized Ca!"-triggered unclamping schemes, and will be run with mutations in the SNARE and Syt components that will be implemented experimentally by our collaborators.