Department of Chemistry, Quantum Theory Project, 2328 New Physics Building, P.O. Box 118435, University of Florida, Gainesville, Florida 32611-8435, USA.
J Phys Chem A. 2009 Oct 29;113(43):11550-9. doi: 10.1021/jp9028722.
The semiempirical quantum mechanical description of NMR chemical shifts has been implemented at the AM1 level with NMR-specific parameters to reproduce experimental (1)H and (13)C NMR chemical shifts. The methodology adopted here is formally the same as that of the previously published finite perturbation theory GIAO-MNDO-NMR approach [Wang, B.; et al. J. Chem. Phys. 2004, 120, 24.]. The primary impetus for this parametrization was the accurate capture of chemical environments of atoms in biological systems. Protein-specific parameters were developed on a training set that comprised five globular protein systems with varied secondary structure and a range in size from 46-61 amino acid residues. A separate set of parameters was developed using a training set of small organic compounds with an emphasis on functional groups that are relevant to biological studies. Our approach can be employed using semiempirical (AM1) geometries and can be executed at a fraction of the cost of ab initio and DFT methods, thus providing an attractive option for the computational NMR studies of much larger protein systems. Analysis carried out on 3340 (1)H and 2233 (13)C chemical shifts for protein systems shows significant improvement over the standard AM1 parameters. Using (1)H and (13)C specific parameters, the rms errors are from 1.05 and 21.28 ppm to 0.62 and 4.83 ppm for hydrogen and carbon, respectively.
NMR 化学位移的半经验量子力学描述已在 AM1 水平上实现,具有 NMR 特异性参数,以重现实验 (1)H 和 (13)C NMR 化学位移。这里采用的方法在形式上与先前发表的有限微扰理论 GIAO-MNDO-NMR 方法相同[Wang, B.; 等人。J. Chem. Phys. 2004, 120, 24]。这种参数化的主要动力是准确捕捉生物系统中原子的化学环境。针对包含五个具有不同二级结构和大小范围为 46-61 个氨基酸残基的球状蛋白质系统的训练集开发了蛋白质特异性参数。使用重点关注与生物研究相关的功能基团的小有机化合物的训练集开发了单独的参数集。我们的方法可以使用半经验(AM1)几何形状并以低于从头算和 DFT 方法成本的一小部分执行,因此为更大蛋白质系统的计算 NMR 研究提供了有吸引力的选择。对 3340 个 (1)H 和 2233 个 (13)C 化学位移进行的分析表明,与标准 AM1 参数相比,有了显著的改善。使用 (1)H 和 (13)C 特异性参数,氢和碳的均方根误差分别从 1.05 和 21.28 ppm 降低到 0.62 和 4.83 ppm。