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Speed of Conformational Change: Comparing Explicit and Implicit Solvent Molecular Dynamics Simulations

机译:构象变化的速度:显式和隐式溶剂分子动力学模拟的比较

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摘要

Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between ∼1- and ∼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, ∼1- to 60-fold, and ∼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.
机译:在原子模拟中,构象空间的足够采样仍然具有挑战性,特别是如果溶剂经过明确处理的话。隐式溶剂模拟可以显着加快构象采样。我们比较了每类的两种常用方法之间的构象采样速度:带有TIP3P水模型的显式溶剂网格Ewald(PME)和流行的广义Born(GB)隐式溶剂模型(在AMBER软件包中实现)。我们系统地研究了小(蛋白质的二面角翻转),大(核小体尾巴塌陷和DNA解缠)和混合(小蛋白质的折叠)构象变化,其标称模拟时间范围从纳秒到微秒,视系统大小而定。相对于PME仿真,GB的构象采样的加速高度依赖于系统和问题。在PME和GB的模拟温度相同的情况下,相应的提速约为1倍(构象变化很小),在1到100倍之间(大变化)和7倍左右(混合情况)。对于小蛋白折叠的情况,将详细讨论温度对加速比和自由能态的影响,溶剂模型之间可能会大不相同。除了加速构象采样外,由于算法差异,根据溶质和溶剂原子的数量,对于小型系统,隐式溶剂模型的计算速度可能更快,对于大型系统,隐式溶剂模型的计算速度也会更慢。对于此处考虑的构象变化,在隐式溶剂提供的低溶剂粘度条件下,组合的加速比分别约为两倍,约1至60倍和约50倍。对于所有研究的系统,1)构象采样加速随着朗文蛋白碰撞频率(有效粘度)的降低而增加; 2)构象采样加速主要是由于溶剂粘度降低,而不是由于溶剂模型之间的自由能态可能存在差异。

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