Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-Bonded Interactions
Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-Bonded Interactions
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DOI：
10.1021/acs.jctc.8b00223
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发表时间：
2018-06-01
影响因子：
5.5
通讯作者：
Shirts, Michael R.
中科院分区：
文献类型：
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作者：
Messerly, Richard A.;Razavi, S. Mostafa;Shirts, Michael R.
在这项研究中，我们提出了一种快速的力场参数化和非键相互作用参数的不确定性量化的方法。从分子模拟得到的大多数热物理性质，特别是汽液平衡(VLE)的准确性很大程度上依赖于非键相互作用。传统上，非键相互作用是通过执行大量的直接分子模拟来参数化以符合宏观性质。由于分子模拟的计算成本，替代模型(即逼近直接分子模拟结果的高效模型)是高维参数化和非键相互作用不确定性量化的重要工具。本研究比较了两种不同的基于配置抽样的代理模型，即多态Bennett接受率(MBAR)和配对相关函数重定标法(PCFR)。MBAR和PCFR与等温等容线(ITIC)热力学积分法相结合，用于估算汽液饱和性质。我们发现mbar和PCFR在它们的作用上是互补的。具体地说，当探索参数空间的较远区域时，PCFR是首选的，而MBAR在本地域中是较好的。
In this study, we present an approach for rapid force field parameterization and uncertainty quantification of the non-bonded interaction parameters for classical force fields. The accuracy of most thermophysical properties, and especially vapor-liquid equilibria (VLE), obtained from molecular simulation depends strongly on the non-bonded interactions. Traditionally, non-bonded interactions are parameterized to agree with macroscopic properties by performing large amounts of direct molecular simulation. Due to the computational cost of molecular simulation, surrogate models (i.e., efficient models that approximate direct molecular simulation results) are an essential tool for high-dimensional parameterization and uncertainty quantification of non-bonded interactions. The present study compares two different configuration-sampling-based surrogate models, namely, Multistate Bennett Acceptance Ratio (MBAR) and Pair Correlation Function Rescaling (PCFR). MBAR and PCFR are coupled with the Isothermal Isochoric (ITIC) thermodynamic integration method for estimating vapor-liquid saturation properties. We find that MBAR and PCFR are complementary in their roles. Specifically, PCFR is preferred when exploring distant regions of the parameter space while MBAR is better in the local domain.