Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland , 9600 Gudelsky Drive, Rockville, Maryland 20850, United States.
Anal Chem. 2017 Nov 7;89(21):11839-11845. doi: 10.1021/acs.analchem.7b03571. Epub 2017 Oct 14.
Two-dimensional (2D) H-C methyl NMR provides a powerful tool to probe the higher order structure (HOS) of monoclonal antibodies (mAbs), since spectra can readily be acquired on intact mAbs at natural isotopic abundance, and small changes in chemical environment and structure give rise to observable changes in corresponding spectra, which can be interpreted at atomic resolution. This makes it possible to apply 2D NMR spectral fingerprinting approaches directly to drug products in order to systematically characterize structure and excipient effects. Systematic collections of NMR spectra are often analyzed in terms of the changes in specifically identified peak positions, as well as changes in peak height and line widths. A complementary approach is to apply principal component analysis (PCA) directly to the matrix of spectral data, correlating spectra according to similarities and differences in their overall shapes, rather than according to parameters of individually identified peaks. This is particularly well-suited for spectra of mAbs, where some of the individual peaks might not be well resolved. Here we demonstrate the performance of the PCA method for discriminating structural variation among systematic sets of 2D NMR fingerprint spectra using the NISTmAb and illustrate how spectral variability identified by PCA may be correlated to structure.
二维（2D）H-C 甲基 NMR 为探测单克隆抗体（mAbs）的高级结构（HOS）提供了强大的工具，因为可以在自然同位素丰度下轻易地在完整 mAbs 上获取光谱，并且化学环境和结构的微小变化会导致相应光谱中可观察到的变化，这些变化可以在原子分辨率下进行解释。这使得可以直接将 2D NMR 光谱指纹图谱方法应用于药物产品，以系统地表征结构和赋形剂效应。通常，根据特定标识峰位置的变化以及峰高和线宽的变化，对 NMR 光谱的系统收集进行分析。另一种补充方法是直接将主成分分析（PCA）应用于光谱数据矩阵，根据整体形状的相似性和差异性对光谱进行关联，而不是根据单独标识峰的参数进行关联。这对于 mAbs 的光谱特别适用，因为其中一些个别峰可能无法很好地分辨。在这里，我们使用 NISTmAb 来演示 PCA 方法在区分系统 2D NMR 指纹图谱中结构变化方面的性能，并说明 PCA 识别的光谱可变性如何与结构相关联。
