Department of Chemistry, Indiana University , Bloomington, Indiana 47405, United States.
J Chem Theory Comput. 2017 Mar 14;13(3):1147-1158. doi: 10.1021/acs.jctc.6b00922. Epub 2017 Feb 14.
We present an efficient implementation of the molecules-in-molecules (MIM) fragment-based quantum chemical method for the evaluation of NMR chemical shifts of large biomolecules. Density functional techniques have been employed in conjunction with large basis sets and including the effects of the solvent environment in these calculations. The MIM-NMR method is initially benchmarked on a set of (alanine) conformers containing strong intramolecular interactions. The incorporation of a second low level of theory to recover the missing long-range interactions in the primary fragmentation scheme is critical to yield reliable chemical shifts, with a mean absolute deviation (MAD) from direct unfragmented calculations of 0.01 ppm for H chemical shifts and 0.07 ppm for C chemical shifts. In addition, the performance of MIM-NMR has been assessed on two large peptides: the helical portion of ubiquitin ( 1UBQ ) containing 12 residues where the X-ray structure is known, and E6-binding protein of papilloma virus ( 1RIJ ) containing 23 residues where the structure has been derived from solution-phase NMR analysis. The solvation environment is incorporated in these MIM-NMR calculations, either through an explicit, implicit, or a combination of both solvation models. Using an explicit treatment of the solvent molecules within the first solvation sphere (3 Å) and an implicit solvation model for the rest of the interactions, the H and C chemical shifts of ubiquitin show excellent agreement with experiment (mean absolute deviation of 0.31 ppm for H and 1.72 ppm for C), while the larger E6-binding protein yields a mean absolute deviation of 0.34 ppm for H chemical shifts. The proposed MIM-NMR method is computationally cost-effective and provides a substantial speedup relative to conventional full calculations, the largest density functional NMR calculation included in this work involving more than 600 atoms and over 10,000 basis functions. The MIM-NMR solvation protocols developed in this work may pave the way for very accurate de novo prediction of NMR chemical shifts of a range of large biomolecules in the future.
我们提出了一种有效的分子在分子(MIM)基于片段的量子化学方法的实现,用于评估大生物分子的 NMR 化学位移。在这些计算中,密度泛函技术与大型基组一起使用,并包括溶剂环境的影响。MIM-NMR 方法最初在一组包含强分子内相互作用的(丙氨酸)构象上进行了基准测试。在主要碎片方案中引入第二个低水平理论来恢复缺失的远程相互作用对于产生可靠的化学位移至关重要,对于 H 化学位移的平均绝对偏差(MAD)为 0.01 ppm,对于 C 化学位移的平均绝对偏差为 0.07 ppm,与直接无碎片计算相比。此外,MIM-NMR 的性能已在两个大型肽上进行了评估:已知 X 射线结构的泛素(1UBQ)的螺旋部分,含有 12 个残基,以及源自溶液相 NMR 分析的乳头瘤病毒(1RIJ)的 E6 结合蛋白,含有 23 个残基。在这些 MIM-NMR 计算中,将溶剂环境包含在溶剂分子中,要么通过显式、隐式或两者的组合来进行。使用第一溶剂球(3 Å)内溶剂分子的显式处理以及其余相互作用的隐式溶剂模型,泛素的 H 和 C 化学位移与实验非常吻合(H 的平均绝对偏差为 0.31 ppm,C 的平均绝对偏差为 1.72 ppm),而较大的 E6 结合蛋白的 H 化学位移的平均绝对偏差为 0.34 ppm。所提出的 MIM-NMR 方法具有计算成本效益,并相对于传统的全计算提供了实质性的加速,这项工作中包含的最大密度泛函 NMR 计算涉及超过 600 个原子和超过 10000 个基函数。本工作中开发的 MIM-NMR 溶剂化方案可能为未来一系列大生物分子的 NMR 化学位移的从头预测铺平道路。