标题： 基于格点聚合物的优化Wang-Landau采样：HP模型蛋白质的基态搜索与折叠热力学 显示英文标题

标题： Optimized Wang-Landau sampling of lattice polymers: Ground state search and folding thermodynamics of HP model proteins

摘要： 粗粒度（晶格）模型在帮助解读蛋白质的物理或生物复杂性方面有着悠久的传统。 尽管这些模型很简单，但数值模拟通常计算需求很大，寻找高效算法的问题与这些模型本身一样古老。 扩展我们之前的工作[ T. Wüst 和 D. P. Landau, Phys. Rev. Lett. 102, 178101 (2009) ]，我们展示了一种基于Wang-Landau采样的蒙特卡罗方法的完整图景，该方法结合了高效的尝试移动（拉伸、键重新桥接和旋转移动），特别适合研究如疏水-极性（HP）晶格模型这样的模型。 通过这种通用且完全盲目的蒙特卡罗过程，可以找到目前所有已知的最难基准HP序列的潜在基态。 对于大多数序列，我们还可以确定整个能量状态密度，并结合适当设计的结构可观测量，探索在几乎无法接近的低温区域中的热力学和复杂的折叠行为。 我们分析了序列长度高达500个残基的随机和蛋白质样异聚物之间的差异。 我们的方法在鲁棒性和速度方面都很强大，但同时也足够灵活和简单，可用于研究蛋白质折叠中的许多相关问题。 显示英文摘要

摘要： Coarse-grained (lattice-) models have a long tradition in aiding efforts to decipher the physical or biological complexity of proteins. Despite the simplicity of these models, however, numerical simulations are often computationally very demanding and the quest for efficient algorithms is as old as the models themselves. Expanding on our previous work [T. W\"ust and D. P. Landau, Phys. Rev. Lett. 102, 178101 (2009)], we present a complete picture of a Monte Carlo method based on Wang-Landau sampling in combination with efficient trial moves (pull, bond-rebridging and pivot moves) which is particularly suited to the study of models such as the hydrophobic-polar (HP) lattice model of protein folding. With this generic and fully blind Monte Carlo procedure, all currently known putative ground states for the most difficult benchmark HP sequences could be found. For most sequences we could also determine the entire energy density of states and, together with suitably designed structural observables, explore the thermodynamics and intricate folding behavior in the virtually inaccessible low-temperature regime. We analyze the differences between random and protein-like heteropolymers for sequence lengths up to 500 residues. Our approach is powerful both in terms of robustness and speed, yet flexible and simple enough for the study of many related problems in protein folding.