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与多维核磁共振方法相比,一维核磁共振在蛋白质治疗药物高阶结构指纹识别方面的分析优势。

On the Analytical Superiority of 1D NMR for Fingerprinting the Higher Order Structure of Protein Therapeutics Compared to Multidimensional NMR Methods.

作者信息

Poppe Leszek, Jordan John B, Rogers Gary, Schnier Paul D

机构信息

†Discovery Attribute Sciences, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California 91320, United States.

‡Product Attribute Sciences, Amgen Inc., One Amgen Center Drive, Thousand Oaks, California 91320, United States.

出版信息

Anal Chem. 2015 Jun 2;87(11):5539-45. doi: 10.1021/acs.analchem.5b00950. Epub 2015 May 14.

Abstract

An important aspect in the analytical characterization of protein therapeutics is the comprehensive characterization of higher order structure (HOS). Nuclear magnetic resonance (NMR) is arguably the most sensitive method for fingerprinting HOS of a protein in solution. Traditionally, (1)H-(15)N or (1)H-(13)C correlation spectra are used as a "structural fingerprint" of HOS. Here, we demonstrate that protein fingerprint by line shape enhancement (PROFILE), a 1D (1)H NMR spectroscopy fingerprinting approach, is superior to traditional two-dimensional methods using monoclonal antibody samples and a heavily glycosylated protein therapeutic (Epoetin Alfa). PROFILE generates a high resolution structural fingerprint of a therapeutic protein in a fraction of the time required for a 2D NMR experiment. The cross-correlation analysis of PROFILE spectra allows one to distinguish contributions from HOS vs protein heterogeneity, which is difficult to accomplish by 2D NMR. We demonstrate that the major analytical limitation of two-dimensional methods is poor selectivity, which renders these approaches problematic for the purpose of fingerprinting large biological macromolecules.

摘要

蛋白质治疗药物分析表征的一个重要方面是高阶结构(HOS)的全面表征。核磁共振(NMR)可以说是用于对溶液中蛋白质的高阶结构进行指纹识别的最灵敏方法。传统上,1H-15N或1H-13C相关谱被用作高阶结构的“结构指纹”。在此,我们证明了通过线形增强进行蛋白质指纹识别(PROFILE),一种一维1H NMR光谱指纹识别方法,优于使用单克隆抗体样品和高度糖基化蛋白质治疗药物(阿法依泊汀)的传统二维方法。PROFILE在二维NMR实验所需时间的一小部分内就能生成治疗性蛋白质的高分辨率结构指纹。PROFILE谱的交叉相关分析使人们能够区分高阶结构与蛋白质异质性的贡献,而这是二维NMR难以做到的。我们证明二维方法的主要分析局限性在于选择性差,这使得这些方法在对大型生物大分子进行指纹识别时存在问题。

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