An Automated Proteoform Characterization Control System

自动化蛋白质形态表征控制系统

• 批准号: 10010454
• 负责人: Kenneth Durbin
• 金额: $ 20.2万
• 依托单位: PROTEINACEOUS, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10010454
• 关键词: Amino Acid Sequence; Biological; Biotechnology; Charge; Collection; Computer software; Consumption; Custom; Data; Data Analyses; Data Set; Databases; Decision Making; Disease; Escherichia coli; Family; Feedback; Generations; Genes; Grant; Immunoprecipitation; Industry; Intelligence; Knowledge; Laboratories; Manuals; Mass Spectrum Analysis; Modeling; Molecular Weight; Names; Output; Peptides; Phase; Post-Translational Protein Processing; Probability; Procedures; Property; Proteins; Proteomics; Reporting; Research; Research Personnel; Resolution; Running; Sampling; Scanning; Scientist; Small Business Innovation Research Grant; Speed; Sum; Surveys; System; Technology; Testing; Time; Universities; Update; Validation; Variant; Visualization software; base; computerized data processing; data acquisition; data visualization; drug development; experimental study; flexibility; follow-up; insight; instrument; interest; mass spectrometer; novel; software systems; stem; success; therapeutic protein; tool

ABSTRACT Current mass spectrometers have benefited from a technological revolution over recent years, with great increases to speed and resolution as well as significant improvements in fragmentation capabilities for biomolecule analyses. Proteomics results that were previously unthinkable only a few years ago are now routine and being performed by hundreds of laboratories across the world. However, despite these advancements and successes, the software systems guiding mass spectrometry data acquisition have not seen technology improvements on the same scale. As such, these new mass spectrometers have not yet reached their full potential, particularly for intact protein characterization where analytes are more varied than peptides and acquisition parameters are tougher to generalize. A software named AutoProt is being developed to automate the targeted characterization of proteoforms from a proteoform family. AutoProt controls the acquisition of mass spectrometry data, initiating a data-driven fragmentation routine when proteoforms-of-interest from a proteoform family are detected in survey scans. As each fragmentation data scan is collected, AutoProt matches experimental data to theoretical proteoform fragments and uses the corresponding results to make an informed decision on how to further characterize the proteoform. By using instant feedback, fragmentation settings are customized specifically and in real-time for each proteoform being analyzed, leading to better characterization results in less overall time. In Phase I, AutoProt will be further developed to handle the characterization of multiple proteoforms such as modified and truncated forms from the same proteoform family in the same acquisition run, enabling a wider assessment of the proteoforms present in a sample (e.g., all the proteoforms from the same UniProt gene accession after immunoprecipitation). A database will be integrated into AutoProt to store run data and allow sample characterization to be resumed for additional acquisition runs. Furthermore, the characterization routine will be made more robust in this grant through the collection of a large amount of fragmentation data on many proteoforms and then the distillation of that data into a general fragmentation model. AutoProt will then be able to broadly characterize proteoforms with different properties (e.g., molecular weight and fragmentation propensities). Lastly, AutoProt will be outfitted with report generation to automatically output experimental report files compatible with the proteoform data visualization tool, TDCollider. With these features in place, AutoProt will be a first-of-its-kind automated characterization software with first-class proteoform characterization abilities and acquisition-to-report capabilities, eliminating time- consuming set up of acquisition and processing for proteoform characterization data.

摘要 目前的质谱仪受益于近年来的技术革命， 速度和分辨率的提高以及碎片化能力的显著改进， 生物分子分析蛋白质组学的研究结果在几年前还是不可想象的，但现在已经成为了常规 并由世界各地数百个实验室进行。然而，尽管这些进步和 成功，指导质谱数据采集的软件系统还没有看到技术 同样规模的改进。因此，这些新的质谱仪尚未充分发挥其潜力， 特别是对于完整蛋白质表征，其中分析物比肽变化更大， 参数更难概括。正在开发一种名为AutoProt的软件， 来自蛋白质型家族的蛋白质型的表征。AutoProt控制质量采集 当来自质谱数据的感兴趣的蛋白质型不存在时，启动数据驱动的片段化例程。 Proteoform家族在调查扫描中被检测到。在收集每个碎片数据扫描时，AutoProt会匹配 实验数据的理论proteoform片段，并使用相应的结果，使一个知情的 决定如何进一步表征蛋白形式。通过使用即时反馈， 为每种被分析的蛋白质型进行专门和实时定制，从而更好地表征 导致总时间更少。在第一阶段，AutoProt将得到进一步开发，以处理以下内容的表征 多种蛋白质形式，例如来自同一蛋白质家族的修饰形式和截短形式 采集运行，能够更广泛地评估样品中存在的蛋白质型（例如，所有的蛋白质 来自免疫沉淀后的相同UniProt基因登录）。数据库将集成到AutoProt中 以存储运行数据并允许恢复样品表征以进行额外的采集运行。此外，委员会认为， 通过收集大量的 许多蛋白质组的碎片数据，然后将该数据蒸馏成一般碎片 模型然后，AutoProt将能够广泛地表征具有不同性质的蛋白形式（例如，分子 重量和碎裂倾向）。最后，AutoProt将配备报告生成功能， 自动输出与Proteoform数据可视化工具兼容的实验报告文件， TDCollider。有了这些功能，AutoProt将成为第一款自动化表征软件 具有一流的蛋白质形态表征能力和采集到报告能力， 用于蛋白形式表征数据的采集和处理的消费设置。