Institute for Molecular Bioscience , The University of Queensland , Brisbane , Queensland 4072 , Australia.
J Phys Chem B. 2019 Mar 7;123(9):1903-1912. doi: 10.1021/acs.jpcb.8b10649. Epub 2019 Feb 21.
Disulfide-rich peptides are a class of molecules for which NMR spectroscopy has been the primary tool for structural characterization. Here, we explore whether the process can be achieved by using structural information encoded in chemical shifts. We examine (i) a representative set of five cyclic disulfide-rich peptides that have high-resolution NMR and X-ray structures and (ii) a larger set of 100 disulfide-rich peptides from the PDB. Accuracy of the calculated structures was dependent on the methods used for searching through conformational space and for identifying native conformations. Although Hα chemical shifts could be predicted reasonably well using SHIFTX, agreement between predicted and experimental chemical shifts was sufficient for identifying native conformations for only some peptides in the representative set. Combining chemical shift data with the secondary structure information and potential energy calculations improved the ability to identify native conformations. Additional use of sparse distance restraints or homology information to restrict the search space also improved the resolution of the calculated structures. This study demonstrates that abbreviated methods have potential for elucidation of peptide structures to high resolution and further optimization of these methods, e.g., improvement in chemical shift prediction accuracy, will likely help transition these methods into the mainstream of disulfide-rich peptide structural biology.
富含二硫键的肽是一类分子,其结构特征主要通过核磁共振波谱法来确定。在这里,我们探讨了是否可以通过利用化学位移中编码的结构信息来实现这一过程。我们研究了(i)具有高分辨率 NMR 和 X 射线结构的 5 个代表性环状富含二硫键的肽,以及(ii)来自 PDB 的 100 个富含二硫键的肽的更大集合。计算结构的准确性取决于用于搜索构象空间和识别天然构象的方法。尽管使用 SHIFTX 可以相当准确地预测 Hα化学位移,但预测的化学位移与实验化学位移之间的一致性足以识别代表性集合中仅部分肽的天然构象。将化学位移数据与二级结构信息和势能计算相结合,可以提高识别天然构象的能力。进一步使用稀疏距离约束或同源信息来限制搜索空间也可以提高计算结构的分辨率。这项研究表明,简化方法有可能阐明高分辨率的肽结构,并且进一步优化这些方法,例如提高化学位移预测的准确性,可能有助于将这些方法引入富含二硫键的肽结构生物学的主流。