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GPU-accelerated analysis and visualization of large structures solved by molecular dynamics flexible fitting

机译:GPU加速的大型结构分析和可视化,通过分子动力学灵活拟合解决

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Hybrid structure fitting methods combine data from cryo-electron microscopy and X-ray crystallography with molecular dynamics simulations for the determination of all-atom structures of large biomolecular complexes. Evaluating the quality-of-fit obtained from hybrid fitting is computationally demanding, particularly in the context of a multiplicity of structural conformations that must be evaluated. Existing tools for quality-of-fit analysis and visualization have previously targeted small structures and are too slow to be used interactively for large biomolecular complexes of particular interest today such as viruses or for long molecular dynamics trajectories as they arise in protein folding. We present new data-parallel and GPU-accelerated algorithms for rapid interactive computation of quality-of-fit metrics linking all-atom structures and molecular dynamics trajectories to experimentally-determined density maps obtained from cryo-electron microscopy or X-ray crystallography. We evaluate the performance and accuracy of the new quality-of-fit analysis algorithms vis-a-vis existing tools, examine algorithm performance on GPU-accelerated desktop workstations and supercomputers, and describe new visualization techniques for results of hybrid structure fitting methods.
机译:混合结构拟合方法将来自低温电子显微镜和X射线晶体学的数据与分子动力学模拟相结合,以确定大型生物分子复合物的全原子结构。评估从混合拟合获得的拟合质量是计算上的需求,特别是在必须评估的多个结构构象的情况下。现有的适合质量分析和可视化的工具以前以小结构为目标,并且太慢了,无法交互式地用于当今特别感兴趣的大型生物分子复合物(例如病毒)或蛋白质折叠中出现的长分子动力学轨迹。我们提出了新的数据并行和GPU加速算法,用于快速交互式计算适合质量的度量,该度量将所有原子结构和分子动力学轨迹链接到从低温电子显微镜或X射线晶体学获得的实验确定的密度图。相对于现有工具,我们评估了新的拟合质量分析算法的性能和准确性,检查了GPU加速的台式工作站和超级计算机上的算法性能,并描述了混合结构拟合方法结果的新型可视化技术。

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