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采用 B3LYP/cc-pVDZ 和经验导出的系统误差校正项开发 13C NMR 化学位移预测程序:一种计算小分子结构解析方法。

Development of a C NMR Chemical Shift Prediction Procedure Using B3LYP/cc-pVDZ and Empirically Derived Systematic Error Correction Terms: A Computational Small Molecule Structure Elucidation Method.

机构信息

Material and Analytical Sciences, Boehringer Ingelheim Pharmaceuticals, Inc. , Ridgefield, Connecticut 06877, United States.

Chemical Development, Boehringer Ingelheim Pharmaceuticals, Inc. , Ridgefield, Connecticut 06877, United States.

出版信息

J Org Chem. 2017 May 19;82(10):5135-5145. doi: 10.1021/acs.joc.7b00321. Epub 2017 May 2.

DOI:10.1021/acs.joc.7b00321
PMID:28398046
Abstract

An accurate and efficient procedure was developed for performing C NMR chemical shift calculations employing density functional theory with the gauge invariant atomic orbitals (DFT-GIAO). Benchmarking analysis was carried out, incorporating several density functionals and basis sets commonly used for prediction of C NMR chemical shifts, from which the B3LYP/cc-pVDZ level of theory was found to provide accurate results at low computational cost. Statistical analyses from a large data set of C NMR chemical shifts in DMSO are presented with TMS as the calculated reference and with empirical scaling parameters obtained from a linear regression analysis. Systematic errors were observed locally for key functional groups and carbon types, and correction factors were determined. The application of this process and associated correction factors enabled assignment of the correct structures of therapeutically relevant compounds in cases where experimental data yielded inconclusive or ambiguous results. Overall, the use of B3LYP/cc-pVDZ with linear scaling and correction terms affords a powerful and efficient tool for structure elucidation.

摘要

开发了一种准确高效的程序,用于通过具有规范不变原子轨道(DFT-GIAO)的密度泛函理论进行 13C NMR 化学位移计算。进行了基准分析,其中包括几种常用的密度泛函和基组,用于预测 13C NMR 化学位移,结果发现 B3LYP/cc-pVDZ 理论水平在低计算成本下提供了准确的结果。从 DMSO 中 13C NMR 化学位移的大数据集中呈现了统计分析,其中 TMS 作为计算参考,并从线性回归分析中获得了经验缩放参数。对于关键官能团和碳类型,观察到局部存在系统误差,并确定了校正因子。在实验数据产生不确定或模棱两可的结果的情况下,该过程和相关校正因子的应用可用于确定治疗相关化合物的正确结构。总的来说,使用 B3LYP/cc-pVDZ 与线性标度和校正项为结构阐明提供了强大而高效的工具。

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