Energies, Geometries, and Charge Distributions of Zn Molecules, Clusters, and Biocenters from Coupled Cluster, Density Functional, and Neglect of Diatomic Differential Overlap Models

耦合簇 双原子分子 偶极子 化学 键离解能 粘结长度 基准集 密度泛函理论 离解(化学) 星团(航天器) 结合能 原子物理学 分子 计算化学 分子物理学 物理 物理化学 计算机科学 有机化学 程序设计语言
作者
Anastassia Sorkin,Donald G. Truhlar,Elizabeth A. Amin
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:5 (5): 1254-1265 被引量:66
标识
DOI:10.1021/ct900038m
摘要

We present benchmark databases of Zn-ligand bond distances, bond angles, dipole moments, and bond dissociation energies for Zn-containing small molecules and Zn coordination compounds with H, CH3, C2H5, NH3, O, OH, H2O, F, Cl, S, and SCH3 ligands. The test set also includes clusters with Zn-Zn bonds. In addition, we calculated dipole moments and binding energies for Zn centers in coordination environments taken from zinc metalloenzyme X-ray structures, representing both structural and catalytic zinc centers. The benchmark values are based on relativistic-core coupled cluster calculations. These benchmark calculations are used to test the predictions of four density functionals, namely B3LYP and the more recently developed M05-2X, M06, and M06-2X levels of theory, and six semiempirical methods, including neglect of diatomic differential overlap (NDDO) calculations incorporating the new PM3 parameter set for Zn called ZnB, developed by Brothers and co-workers, and the recent PM6 parametrization of Stewart. We found that the best DFT method to reproduce dipole moments and dissociation energies of our Zn compound database is M05-2X, which is consistent with a previous study employing a much smaller and less diverse database and a much larger set of density functionals. Here we show that M05-2X geometries and single-point coupled cluster calculations with M05-2X geometries can also be used as benchmarks for larger compounds, where coupled cluster optimization is impractical, and in particular we use this strategy to extend the geometry, binding energy, and dipole moment databases to additional molecules, and we extend the tests involving crystal-site coordination compounds to two additional proteins. We find that the most predictive NDDO methods for our training set are PM3 and MNDO/d. Notably, we also find large errors in B3LYP for the coordination compounds based on experimental X-ray geometries.
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