New Methods for Large-scale Computer Simulation

项目摘要 仅仅根据蛋白质的一级序列来预测蛋白质的三维结构仍然是一种 现代计算生物学中的重大而难以捉摸的挑战。分子动力学模拟具有很高的 承诺在分子细节上预测蛋白质结构和折叠路径。免疫组织化学的最新进展 经过验证的计算机硬件和改进的采样方法使从头开始折叠蛋白质成为可能 大号的。改进的计算机硬件的亮点是Anton，一个大规模并行的专用 由D.E.Shaw Research设计的超级计算机。Anton成功折叠日本血吸虫D14A快速折叠突变体 80个残基的L抑制因子，它是在μS的643μS长模拟中在49微秒内实现的。论 另一方面，增强抽样方法的最新进展表现为单拷贝连续抽样 PI小组提出的模拟回火(CST)方法。克劳斯·舒尔滕博士的团队- 将CST方法放入NAMD包中，该包重复折叠80个残基的L-抑制子HG突变体 从0.5和4μ的全扩展构象到自然态，S在10μS与钙根的长模拟中. 在传统计算平台上的均方差(Ca-RMSD)为1.7？与之形成鲜明对比的是， 使用ANTON在多个温度下也没有观察到相同蛋白质的完全折叠，即使在100μS- 长时间的模拟。CST在折叠模拟中的这一性能是任何其他SAM-Sm-s都无法比拟的。 在传统计算平台上用于类似目的的采样方法。最近，为了进一步增强 采样效率在研究较大系统时，PI已开发出功能更强大的并行CST(PCST) 方法。初步的Trp-Cage的从头算折叠模拟清楚地表明，PCST在易用性方面是有效的。 适应多个折叠和展开事件甚至大大优于CST。PCST方法 为拟议的三个具体目标的研究奠定了坚实的基础：1)。PCST的发展历程 2)强化采样方法；一种先进的变温约束方案设计 3)有针对性的抽样。高效目标选择的改进盲模型选择方法的研究进展 选择。我们深入的初步研究表明，这些新方法的表现明显优于现有的所有方法- ING方法，并为拟议的研究提供了很高的成功前景。最终，这些强大的 新的算法将为蛋白质模拟提供急需的工具，并提供有效的解决方案 实验X射线结晶学和电子冷冻显微镜中的结构改进。

Project Summary To predict the three-dimensional structures of a protein solely from its primary sequence remains a grand and elusive challenge in modern computational biology. Molecular dynamics simulation has a high promise for predicting protein structures and folding pathways at molecular details. Recent advances in im- proved computer hardware and enhanced sampling methods have made it possible to ab initio fold proteins of larger size. The highlight of the improved computer hardware is Anton, a massively parallel special-purpose supercomputer designed by D.E. Shaw Research. Anton successfully folded the D14A fast-folding mutant of the 80-residue l-repressor, which was achieved at 49 microseconds (μs) in 643μs-long simulations. On the other hand, the latest advance in enhanced sampling methods is represented by the single-copy continuous simulated tempering (CST) method developed by the PI’s group. The group of Dr. Klaus Schulten incorpo- rated the CST method into the NAMD package, which repeatedly folded the 80-residue l-repressor HG mutant from a fully extended conformation to the native state at 0.5 and 4μs in 10μs-long simulations with Ca root- mean-square deviations (Ca-RMSD) of 1.7 Å on a conventional computing platform. In marked contrast, a complete folding of the same protein was NOT observed using Anton at multiple temperatures even in 100μs- long simulations. This performance of CST in folding simulation has never been matched by any other sam- pling method for similar purposes on conventional computing platforms. Most recently, to further enhance sampling efficiencies in studying larger systems, the PI has developed a more powerful parallel CST (PCST) method. Initial ab initio folding simulation of trp-cage clearly demonstrated that the efficiency of PCST in facili- tating multiple folding and unfolding events was even drastically superior to that of CST. The PCST method serves as a solid foundation for the proposed research in three Specific Aims: 1). Development of the PCST method for enhanced sampling; 2). Design of advanced temperature-dependent restraint schemes for targeted sampling; 3). Development of advanced blind model selection methods for efficient target se- lection. Our in-depth preliminary studies demonstrate that these new methods clearly outperformed all exist- ing methods and suggest a high promise of success for the proposed research. Ultimately, these powerful new algorithms will provide urgently-needed tools for protein simulations, and offer an effective solution for structural refinement in experimental X-ray crystallography and electron cryo-microscopy.