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溶剂化自由能几何流计算中参数简并和分子形状关系的起源。

Origin of parameter degeneracy and molecular shape relationships in geometric-flow calculations of solvation free energies.

机构信息

Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.

出版信息

J Chem Phys. 2013 Nov 28;139(20):204108. doi: 10.1063/1.4832900.

Abstract

Implicit solvent models are important tools for calculating solvation free energies for chemical and biophysical studies since they require fewer computational resources but can achieve accuracy comparable to that of explicit-solvent models. In past papers, geometric flow-based solvation models have been established for solvation analysis of small and large compounds. In the present work, the use of realistic experiment-based parameter choices for the geometric flow models is studied. We find that the experimental parameters of solvent internal pressure p = 172 MPa and surface tension γ = 72 mN/m produce solvation free energies within 1 RT of the global minimum root-mean-squared deviation from experimental data over the expanded set. Our results demonstrate that experimental values can be used for geometric flow solvent model parameters, thus eliminating the need for additional parameterization. We also examine the correlations between optimal values of p and γ which are strongly anti-correlated. Geometric analysis of the small molecule test set shows that these results are inter-connected with an approximately linear relationship between area and volume in the range of molecular sizes spanned by the data set. In spite of this considerable degeneracy between the surface tension and pressure terms in the model, both terms are important for the broader applicability of the model.

摘要

隐溶剂模型是化学和生物物理研究中计算溶剂化自由能的重要工具,因为它们需要较少的计算资源,但可以达到与显溶剂模型相当的准确性。在过去的论文中,已经建立了基于几何流的溶剂化模型,用于小分子和大分子化合物的溶剂化分析。在本工作中,研究了基于实际实验参数选择的几何流模型的使用。我们发现,溶剂内压 p = 172 MPa 和表面张力 γ = 72 mN/m 的实验参数在扩展数据集上与实验数据的全局最小均方根偏差的溶剂化自由能相差 1 RT 以内。我们的结果表明,可以使用实验值作为几何流溶剂模型参数,从而无需进行额外的参数化。我们还研究了 p 和 γ 的最优值之间的相关性,它们呈强负相关。对小分子测试集的几何分析表明,这些结果与数据集所涵盖的分子尺寸范围内的面积和体积之间的近似线性关系相互关联。尽管模型中表面张力和压力项之间存在相当大的简并性,但这两个项对于模型的更广泛适用性都很重要。

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