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The multiscale coarse-graining method. X. Improved algorithms for constructing coarse-grained potentials for molecular systems

机译:多尺度粗粒度方法。十,构建分子系统粗粒度电势的改进算法

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The multiscale coarse-graining (MS-CG) method uses simulation data for an atomistic model of a system to construct a coarse-grained (CG) potential for a coarse-grained model of the system. The CG potential is a variational approximation for the true potential of mean force of the degrees of freedom retained in the CG model. The variational calculation uses information about the atomistic positions and forces in the simulation data. In principle, the resulting MS-CG potential will be an accurate representation of the true CG potential if the basis set for the variational calculation is complete enough and the canonical distribution of atomistic states is well sampled by the data set. In practice, atomistic configurations that have very high potential energy are not sampled. As a result there usually is a region of CG configuration space that is not sampled and about which the data set contains no information regarding the gradient of the true potential. The MS-CG potential obtained from a variational calculation will not necessarily be accurate in this unsampled region. A priori considerations make it clear that the true CG potential of mean force must be very large and positive in that region. To obtain an MS-CG potential whose behavior in the sampled region is determined by the atomistic data set, and whose behavior in the unsampled region is large and positive, it is necessary to intervene in the variational calculation in some way. In this paper, we discuss and compare two such methods of intervention, which have been used in previous MS-CG calculations for dealing with nonbonded interactions. For the test systems studied, the two methods give similar results and yield MS-CG potentials that are limited in accuracy only by the incompleteness of the basis set and the statistical error of associated with the set of atomistic configurations used. The use of such methods is important for obtaining accurate CG potentials.
机译:多尺度粗粒度(MS-CG)方法使用系统原子模型的模拟数据来构造系统粗粒度模型的粗粒度(CG)电位。 CG电位是CG模型中保留的自由度平均力的真实电位的变分近似值。变分计算使用有关模拟数据中原子位置和力的信息。原则上,如果变分计算的基础集足够完整,并且原子态的规范分布已由数据集很好地采样,则所得的MS-CG势将准确表示真实CG势。实际上,不对具有非常高的势能的原子构型进行采样。结果,通常存在未配置的CG配置空间区域,并且该区域的数据集不包含有关真实电位梯度的信息。从变分计算获得的MS-CG电位在该未采样区域不一定准确。先验的考虑清楚地表明,在该区域中平均力的真实CG潜力必须非常大且为正。为了获得MS-CG电位,该电位在采样区域中的行为由原子数据集确定,并且在未采样区域中的行为较大且为正,因此有必要以某种方式进行变化计算。在本文中,我们讨论并比较了两种此类干预方法,这些方法已在以前的MS-CG计算中用于处理非键相互作用。对于所研究的测试系统,这两种方法给出的结果相似,并且产生的MS-CG电位的准确性仅受基础集的不完整和与所用原子配置集相关的统计误差的限制。使用此类方法对于获得准确的CG电位很重要。

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