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多糖基化生物治疗药物的无数据依赖性氧鎓离子分析。

Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics.

机构信息

a Pharmaceutical Sciences and Research , Momenta Pharmaceuticals , Cambridge , MA , USA.

出版信息

MAbs. 2018 Oct;10(7):968-978. doi: 10.1080/19420862.2018.1494106. Epub 2018 Aug 1.

Abstract

The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necessary to fully analyze multi-glycosylated biotherapeutics. Established glycopeptide methodologies have generally utilized a priori knowledge of the glycosylation states of the investigated protein(s), database searching of results generated from data-dependent liquid chromatography-tandem mass spectrometry workflows, and extracted ion quantitation of the individual identified species. However, the inherent complexity of glycosylation makes predicting all glycoforms on all glycosylation sites extremely challenging, if not impossible. That is, only the "knowns" are assessed. Here, we describe an agnostic methodology to qualitatively and quantitatively assess both "known" and "unknown" site-specific glycosylation for biotherapeutics that contain multiple glycosylation sites. The workflow uses data-independent, all ion fragmentation to generate glycan oxonium ions, which are then extracted across the entirety of the chromatographic timeline to produce a glycan-specific "fingerprint" of the glycoprotein sample. We utilized both HexNAc and sialic acid oxonium ion profiles to quickly assess the presence of Fab glycosylation in a therapeutic monoclonal antibody, as well as for high-throughput comparisons of multi-glycosylated protein drugs derived from different clones to a reference product. An automated method was created to rapidly assess oxonium profiles between samples, and to provide a quantitative assessment of similarity.

摘要

对许多蛋白质治疗药物来说,糖基化的特征描述是必需的。具有多个聚糖附着位点的抗体和抗体样分子的出现,使得聚糖分析变得越来越复杂。因此,需要依赖于位点特异性糖肽分析来充分分析多聚糖基生物治疗药物。已建立的糖肽方法通常利用了对所研究蛋白质的糖基化状态的先验知识,对来自基于数据依赖的液相色谱-串联质谱工作流程的结果进行数据库搜索,并对鉴定出的各个物种进行提取离子定量。然而,糖基化的固有复杂性使得预测所有糖基化位点的所有糖型极其具有挑战性,如果不是不可能的话。也就是说,只能评估“已知”的糖型。在这里,我们描述了一种针对含有多个糖基化位点的生物治疗药物的定性和定量评估“已知”和“未知”位点特异性糖基化的无偏见方法。该工作流程使用数据非依赖性的所有离子碎片化来生成聚糖氧鎓离子,然后在整个色谱时间范围内提取这些离子,以产生糖蛋白样品的糖基化特异性“指纹”。我们利用 HexNAc 和唾液酸氧鎓离子轮廓来快速评估治疗性单克隆抗体中 Fab 糖基化的存在情况,以及对源自不同克隆的多聚糖基蛋白药物与参考产品进行高通量比较。创建了一种自动化方法来快速评估样品之间的氧鎓轮廓,并提供相似性的定量评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c979/6204843/b2bbf00cc762/kmab-10-07-1494106-g001.jpg

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