Analytical and Informatic Approach to Determine Disease-related Glycoforms of Proteins

摘要 蛋白质糖基化的疾病相关改变的生物医学意义已被公认为 一段时间然而，在将这些观察结果转化为强有力的疾病方面仍然存在重大挑战。 生物标志物，并建立详细的分子理解如何改变蛋白质糖基化影响 各种生化相互作用和信号通路，包括蛋白质-药物相互作用。此外，委员会认为， 因为蛋白质糖基化是一系列复杂的非模板驱动的生物合成和 在后处理步骤中，蛋白质糖基化谱是生物分子的复杂网络的产物， 相互作用，因此对代谢信号通路的扰动非常敏感，包括那些 伴随疾病。由于这些原因，蛋白质糖基化的详细分子表征是 在用于疾病的生物标志物发现中以及为了将疾病诱导的生物标志物与疾病相关的目的， 蛋白质糖基化对蛋白质功能的改变。这些努力的关键是强大的分析能力 可以确定蛋白质连接的寡糖的组成和结构及其 在复杂和异质混合物中的蛋白质附着位点。一个中心工具， 蛋白质糖基化的表征是串联质谱（MS/MS）的应用， 糖蛋白的蛋白水解消化产生的糖肽。这种分析的一个非常理想的结果是 是获得关于寡糖拓扑结构和多肽序列的信息。目前这款 细节水平通常仅通过以速度为代价组合多个MS/MS方法来实现， 表征的糖肽数量。为了克服这一障碍，我们将开发一种彻底的化学物质， 了解最常见的MS/MS方法--碰撞诱导解离（CID）--如何单独使用 提供关于N-连接糖肽的完整连接信息。我们将开发和应用这一 通过以下方式理解：1）确定电荷状态、单糖组成、氨基酸 组成和振动自由度对糖苷和肽的CID能量要求 质子化N-糖肽中的键断裂; 2）编译和挖掘大数据库的CID谱， 质子化的N-糖肽在不同的碰撞能量，以经验地关联前体离子特性 与能量依赖的解离特性;和3）说明这些方法和见解， 检测人α 1-酸性糖蛋白（AGP）的位点特异性N-糖基化谱的变化， 类风湿性关节炎的症状这些目标的实现将取决于两个组织的能力， 系统生物学核心设施和内布拉斯加州中心的数据管理和分析核心设施， 集成生物分子通信（CIBC）1）获得大型，高维数据集，2）应用 信息学方法来挖掘这些数据集，以了解糖肽解离。这些见解将是 直接适用于阐明由于疾病而产生的位点特异性糖基化模式。

ABSTRACT The biomedical significance of disease-related alterations in protein glycosylation has been recognized for some time. However, significant challenges remain in translating these observations into robust disease biomarkers, and in establishing a detailed molecular understanding of how altered protein glycosylation affects a variety of biochemical interactions and signaling pathways, including protein-drug interactions. Moreover, because protein glycosylation is the end result of a complex series of non-template-driven biosynthetic and post-processing steps, a protein glycosylation profile is the product of an intricate network of biomolecular interactions and is thus exquisitely sensitive to perturbations in metabolic signaling pathways, including those accompanying disease. For these reasons, the detailed molecular characterization of protein glycosylation is of great biomedical interest in biomarker discovery for diseases and for the purpose of relating disease-induced alterations in protein glycosylation to protein function. Essential to such endeavors are powerful analytical techniques that can determine the compositions and structures of protein-linked oligosaccharides and their sites of protein attachment in complex and heterogeneous mixtures. A central tool for the site-specific characterization of protein glycosylation is the application of tandem mass spectrometry (MS/MS) to glycopeptides produced by proteolytic digestion of glycoproteins. A highly desirable outcome of such analyses is to obtain information on both the oligosaccharide topology and the polypeptide sequence. At present, this level of detail is typically achieved only by combining multiple MS/MS methods at the expense of speed and number of glycopeptides characterized. To overcome this barrier, we will develop a thorough chemical understanding of how the most common MS/MS method - collision-induced dissociation (CID) - can alone provide complete connectivity information on N-linked glycopeptides. We will develop and apply this understanding by: 1) establishing the influence of charge state, monosaccharide composition, amino acid composition, and vibrational degrees of freedom on the CID energy requirements for glycosidic and peptide bond scission in protonated N-glycopeptides; 2) compiling and mining a large database of CID spectra of protonated N-glycopeptides at various collision energies to empirically correlate precursor ion characteristics with energy-dependent dissociation characteristics; and 3) illustrating these methods and insights by examining changes in the site-specific N-glycosylation profile of human alpha1-acid glycoprotein (AGP) that occur during rheumatoid arthritis. Achievement of these aims will be enabled by the capabilities of both the Systems Biology Core facility and the Data Management and Analysis Core facility of the Nebraska Center for Integrated Biomolecular Communication (CIBC) to 1) obtain large, high-dimensional data sets, and 2) apply informatic methods to mine these data sets for insights on glycopeptide dissociation. These insights will be directly applicable to the elucidation of site-specific glycosylation patterns that arise as a result of disease.