Development of a rapid glycosylation profiling system using mass spec data

描述（由申请人提供）：本提案的最终目标是开发一种用于糖肽分析的全自动方法，并将该方法应用于几种不同的HIV-Env糖蛋白的分析。这项工作将通过完成三个具体目标来完成：目标1：使用MS数据作为输入，开发一种快速识别单一糖基化糖肽的糖肽组成的算法。目的2：建立一种表征多糖基化糖肽的算法。目的3：使用AIMS 1和2中的工具筛选HIV Env蛋白上可接近的和遗传保守的点。目标1和目标2的大部分工作将通过协同结合质谱数据获取和分析方面的专门知识与软件设计/开发方面的专门知识来完成。这项工作可以广泛影响人类健康研究，因为糖肽分析是一种生物分析技术，可用于筛选疾病或疾病状态的生物标志物;它可用于帮助验证基于糖蛋白的药物的安全性和一致性;它可用于分析HIV包膜蛋白上的糖肽，这是HIV疫苗开发的主要目标。在完成自动糖基化分析系统（目的1和2）后，该系统将用于鉴定与巴顿F博士合作产生的各种HIV- Env候选疫苗上的糖肽组成。杜克大学医学中心的海恩斯。该方法包括制备每种糖蛋白的胰蛋白酶解物，对消化产物进行HPLC-MS和LC-MS/MS分析，并使用开发的糖肽分析软件解释结果。完成这项工作后，Env蛋白的糖肽谱将提供关于Env上表位可及性的信息。这与人类健康有关，因为鉴定在HIV-1进化枝中始终暴露的蛋白质上的表位是设计HIV疫苗的第一步，该疫苗模拟这些表位并产生针对HIV-1的广泛中和抗体。公共卫生相关性：我们的目标是开发快速分析糖肽的工具。糖肽是HIV Env蛋白的组成部分，它们的分析可用于识别病毒表面上的阿基里斯之踵（始终暴露并因此易受抗体攻击的区域）。

DESCRIPTION (provided by applicant): The ultimate goal of this proposal is to develop a fully-automated approach for analysis of glycopeptides and to apply that approach to the analysis of several different HIV-Env glycoproteins. This work would be accomplished by completing three specific aims: AIM 1: Using MS data as the input, develop an algorithm that rapidly identifies glycopeptide compositions for singly glycosylated glycopeptides. AIM 2: Develop an algorithm that characterizes multiply glycosylated glycopeptides. AIM 3: Use the tools in AIMS 1 and 2 to screen for accessible and genetically conserved points on the HIV Env protein. The bulk of the work, Aims 1 and 2, would be completed by synergistically incorporating expertise in mass spectral (MS) data acquisition and analysis with expertise in software design/development. This work can broadly impact human health research because glycopeptide analysis is an enabling bioanalytical technology that can be used to screen for biomarkers of disease or disease state; it can be used to help verify the safety and consistency of glycoprotein-based pharmaceuticals; and it can be used to analyze glycopeptides on HIV Envelope proteins, a major target for HIV vaccine development. After completion of the automated glycosylation profiling system (Aims 1 and 2) this system would be used to identify the glycopeptide composition on a variety of HIV- Env vaccine candidates generated in collaboration with Dr. Barton F. Haynes at Duke University Medical Center. The method for this approach includes preparing tryptic digests of each of the glycoproteins, conducing HPLC-MS and LC-MS/MS analyses on the digested products, and interpreting the results using the developed glycopeptide analysis software. After completion of this work, the glycopeptide profiles of the Env proteins would provide information about epitope accessibility on Env. This is relevant to human health because identifying epitopes on the protein that are consistently exposed across HIV-1 clades is a first step in designing an HIV vaccine that mimics these epitopes and elicits broadly neutralizing antibodies to HIV-1. PUBLIC HEALTH RELEVANCE: We aim to develop tools for the rapid analysis of glycopeptides. Glycopeptides are components of the HIV Env protein, and their analysis could be used to identify Achilles Heels (regions which are consistently exposed and thus vulnerable to antibodies) on the surface of the virus.