A. E. Favorsky Irkutsk Institute of Chemistry, Siberian Branch of the Russian Academy of Sciences, Favorsky St. 1, 664033 Irkutsk, Russia.
Int J Mol Sci. 2024 Oct 1;25(19):10588. doi: 10.3390/ijms251910588.
A root factor for the accuracy of all quantum chemical calculations of nuclear magnetic resonance (NMR) chemical shifts is the quality of the molecular equilibrium geometry used. In turn, this quality depends largely on the basis set employed at the geometry optimization stage. This parameter represents the main subject of the present study, which is a continuation of our recent work, where new pecG- ( = 1, 2) basis sets for the geometry optimization were introduced. A goal of this study was to compare the performance of our geometry-oriented pecG- ( = 1, 2) basis sets against the other basis sets in massive calculations of C NMR shielding constants/chemical shifts in terms of their efficacy in reducing geometry factor errors. The testing was carried out with both large-sized biologically active natural products and medium-sized compounds with complicated electronic structures. The former were treated using the computation protocol based on the density functional theory (DFT) and considered in the theoretical benchmarking, while the latter were treated using the computational scheme based on the upper-hierarchy coupled cluster (CC) methods and were used in the practical benchmarking involving the comparison with experimental NMR data. Both the theoretical and practical analyses showed that the pecG-1 and pecG-2 basis sets resulted in substantially reduced geometry factor errors in the calculated C NMR chemical shifts/shielding constants compared to their commensurate analogs, with the pecG-2 basis set being the best of all the considered basis sets.
所有核磁共振（NMR）化学位移量子化学计算准确性的根本因素是所使用的分子平衡几何形状的质量。反过来，这一质量在很大程度上取决于在几何优化阶段使用的基组。本研究的主题是对我们最近的工作的延续，在该工作中引入了新的 pecG-（=1,2）基组用于几何优化。本研究的目的之一是比较我们的几何导向 pecG-（=1,2）基组与其他基组在大规模计算 C NMR 屏蔽常数/化学位移方面的性能，即它们在降低几何因子误差方面的效果。通过基于密度泛函理论（DFT）的计算方案对前者（大型生物活性天然产物）进行了测试，并将其纳入理论基准测试，而对后者（具有复杂电子结构的中等大小化合物）则采用基于高级耦合簇（CC）方法的计算方案进行测试，并与实验 NMR 数据进行比较。理论和实际分析都表明，与同类基组相比，pecG-1 和 pecG-2 基组在计算的 C NMR 化学位移/屏蔽常数中产生的几何因子误差大大降低，其中 pecG-2 基组是所有考虑基组中最好的。
