Efficient Equilibrium Sampling of All-Atom Peptides Using Library-Based Monte Carlo
Efficient Equilibrium Sampling of All-Atom Peptides Using Library-Based Monte Carlo
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DOI：
10.1021/jp910112d
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发表时间：
2010-05-06
影响因子：
3.3
通讯作者：
Zuckerman, Daniel M.
中科院分区：
文献类型：
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作者：
Ding, Ying;Mamonov, Artem B.;Zuckerman, Daniel M.
我们应用我们以前开发的基于库的Monte Carlo（LBMC）的几个隐式溶剂化的全原子肽的平衡采样。LBMC可以使用预先计算的分子碎片构型和能量的统计库来进行分子的平衡采样。在这项研究中，我们采用了基于残留物的碎片分布根据玻尔兹曼因子的优化潜力液体模拟全原子（OPLS-AA）力场描述的个别片段。采用两种溶剂模型：一个简单的均匀介电和广义玻恩/表面积（GBSA）模型。使用三种不同的统计工具将LBMC的效率与标准朗之万动力学（LD）进行比较。统计分析表明，LBMC比LD快100倍以上，不仅对于简单溶剂模型，而且对于GBSA。
We applied our previously developed library-based Monte Carlo (LBMC) to equilibrium sampling of several implicitly solvated all-atom peptides. LBMC can perform equilibrium sampling of molecules using precalculated statistical libraries of molecular-fragment configurations and energies. For this study, we employed residue-based fragments distributed according to the Boltzmann factor of the optimized potential for liquid simulations all-atom (OPLS-AA) forcefield describing the individual fragments. Two solvent models were employed: a simple uniform dielectric and the generalized Born/surface area (GBSA) model. The efficiency of LBMC was compared to standard Langevin dynamics (LD) using three different statistical tools. The statistical analyses indicate that LBMC is more than 100 times faster than LD not only for the simple solvent model but also for GBSA.