National Institute of Standards and Technology, Institute for Bioscience and Biotechnology Research, Rockville, Maryland.
Curr Protoc Protein Sci. 2020 Jun;100(1):e105. doi: 10.1002/cpps.105.
Characterization of the higher-order structure (HOS) of protein therapeutics, and in particular of monoclonal antibodies, by 2D H- C methyl correlated NMR has been demonstrated as precise and robust. Such characterization can be greatly enhanced when collections of spectra are analyzed using multivariate approaches such as principal component analysis (PCA), allowing for the detection and identification of small structural differences in drug substance that may otherwise fall below the limit of detection of conventional spectral analysis. A major limitation to this approach is the presence of aliphatic signals from formulation or excipient components, which result in spectral interference with the protein signal of interest; however, the recently described Selective Excipient Reduction and Removal (SIERRA) filter greatly reduces this issue. Here we will outline how basic 2D H- C methyl-correlated NMR may be combined with the SIERRA approach to collect 'clean' NMR spectra of formulated monoclonal antibody therapeutics (i.e., drug substance spectra free of interfering component signals), and how series of such spectra may be used for HOS characterization by direct PCA of the series spectral matrix. © 2020 U.S. Government. Basic Protocol 1: NMR data acquisition Basic Protocol 2: Full spectral matrix data processing and analysis Support Protocol: Data visualization and cluster analysis.
通过二维 H- C 甲基相关 NMR 对蛋白质治疗剂（尤其是单克隆抗体）的高级结构（HOS）进行表征已被证明是精确和可靠的。当使用多元分析方法（如主成分分析（PCA））分析光谱集合时，这种表征可以得到极大的增强，从而可以检测和识别药物物质中可能低于常规光谱分析检测限的微小结构差异。这种方法的一个主要限制是制剂或赋形剂成分的脂肪族信号的存在，这会导致与感兴趣的蛋白质信号发生光谱干扰；然而，最近描述的选择性赋形剂减少和去除（SIERRA）过滤器大大减少了这个问题。在这里，我们将概述如何将基本的二维 H- C 甲基相关 NMR 与 SIERRA 方法结合使用，以收集配方单克隆抗体治疗剂的“干净”NMR 光谱（即没有干扰成分信号的药物物质光谱），以及如何通过直接 PCA 对系列光谱矩阵进行 HOS 表征。© 2020 美国政府。基本方案 1：NMR 数据采集基本方案 2：全光谱矩阵数据处理和分析支持方案：数据可视化和聚类分析。
