Department of Chemistry and Zukunftskolleg, University of Konstanz , D-78457 Konstanz, Germany.
Department of Pharmaceutical and Medicinal Chemistry, Institute of Pharmacy , Eberhard Karls University Tübingen, D-72076 Tübingen, Germany.
J Chem Theory Comput. 2012 Apr 10;8(4):1480-92. doi: 10.1021/ct200913r. Epub 2012 Mar 30.
It has been demonstrated that the fragmentation scheme of our adjustable density matrix assembler (ADMA) approach for the quantum chemical calculations of very large systems is well-suited to calculate NMR chemical shifts of proteins [ Frank et al. Proteins2011, 79, 2189-2202 ]. The systematic investigation performed here on the influences of the level of theory, basis set size, inclusion or exclusion of an implicit solvent model, and the use of partial charges to describe additional parts of the macromolecule on the accuracy of NMR chemical shifts demonstrates that using a valence triple-ζ basis set leads to large improvement compared to the results given in the previous publication. Additionally, moving from the B3LYP to the mPW1PW91 density functional and including partial charges and implicit solvents gave the best results with mean absolute errors of 0.44 ppm for hydrogen atoms excluding H(N) atoms and between 1.53 and 3.44 ppm for carbon atoms depending on the size and also on the accuracy of the protein structure. Polar hydrogen and nitrogen atoms are more difficult to predict. For the first, explicit hydrogen bonds to the solvents need to be included and, for the latter, going beyond DFT to post-Hartree-Fock methods like MP2 is probably required. Even if empirical methods like SHIFTX+ show similar performance, our calculations give for the first time very reliable chemical shifts that can also be used for complexes of proteins with small-molecule ligands or DNA/RNA. Therefore, taking advantage of its ab initio nature, our approach opens new fields of application that would otherwise be largely inaccessible due to insufficient availability of data for empirical parametrization.
已经证明，我们的可调密度矩阵组装器（ADMA）方法的碎片化方案非常适合于计算非常大系统的量子化学计算的 NMR 化学位移[Frank 等人，Proteins2011，79，2189-2202]。这里对理论水平、基组大小、是否包含隐溶剂模型以及使用部分电荷来描述大分子的其他部分对 NMR 化学位移精度的影响进行了系统的研究，结果表明，使用价三 ζ 基组与前一篇出版物中给出的结果相比有了很大的改进。此外，从 B3LYP 到 mPW1PW91 密度泛函，包括部分电荷和隐溶剂，给出了最好的结果，对于不包括 H（N）原子的氢原子，平均绝对误差为 0.44ppm，对于碳原子，平均绝对误差在 1.53 到 3.44ppm 之间，这取决于蛋白质结构的大小和精度。极性氢和氮原子更难预测。对于前者，需要包括与溶剂的显式氢键，对于后者，可能需要超越密度泛函理论到后 Hartree-Fock 方法，如 MP2。即使像 SHIFTX+这样的经验方法表现出类似的性能，我们的计算也首次给出了非常可靠的化学位移，这些化学位移也可用于蛋白质与小分子配体或 DNA/RNA 的复合物。因此，利用其从头算性质，我们的方法开辟了新的应用领域，如果没有经验参数化的充分数据可用性，这些领域在很大程度上是无法访问的。
