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用嵌入簇积分方程理论预测互变异构体比例。

Prediction of tautomer ratios by embedded-cluster integral equation theory.

机构信息

Theoretische Physikalische Chemie, Technische Universität Dortmund, Otto-Hahn-Strasse 6, Dortmund, Germany.

出版信息

J Comput Aided Mol Des. 2010 Apr;24(4):343-53. doi: 10.1007/s10822-010-9340-x. Epub 2010 Mar 30.

DOI:10.1007/s10822-010-9340-x
PMID:20352296
Abstract

The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol(-1)) as well as for the full set of quantitative reaction data (2.0 kcal mol(-1)) among the SAMPL2 participants.

摘要

“嵌入式簇参考相互作用位点模型”(EC-RISM)方法将统计力学积分方程理论与量子化学计算相结合,用于预测溶液中化学反应的热力学数据。溶质的电子结构与溶剂的结构自洽地确定,溶剂的结构由 3D RISM 积分方程理论描述。连续的溶剂位点分布被映射到一组离散的背景电荷(“嵌入式簇”)上,这些电荷代表对分子哈密顿量的额外贡献。EC-RISM 对 SAMPL2 互变异构体挑战集的分析分三个阶段进行。首先,选择提供定量实验自由能数据的化合物组,以确定用于几何优化和自由能预测的适当量子化学理论水平。其次,将得到的工作流程应用于整个数据集,允许对结果进行化学解释。第三,部分化合物的实验数据的披露促进了对方法问题的详细分析,并提出了对模型未来改进的建议。在没有专门调整参数的情况下,EC-RISM 模型在 SAMPL2 参与者中为第一组(0.6 kcal mol(-1))和整个定量反应数据集(2.0 kcal mol(-1))产生了最小的均方根误差值。

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Chem Sci. 2021 Jul 19;12(34):11364-11381. doi: 10.1039/d1sc01185e. eCollection 2021 Sep 1.
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