Ultraviolet Photodissociation (UVPD) Spectroscopy of DMS-selected COVID-19 peptide residues

DMS 选择的 COVID-19 肽残基的紫外光解离 (UVPD) 光谱

• 批准号: 554546-2020
• 负责人: Hopkins, Scott
• 金额: $ 3.64万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705481
• 关键词: Ultraviolet; Photodissociation; UVPD; Spectroscopy; DMS

This project involves partnership between researchers at the University of Waterloo and mass spectrometry instrumentation company SCIEX (based in Concord, ON). We propose to use a combinatorial approach involving differential mobility spectrometry (DMS), mass spectrometry (MS), and ultraviolet photodissociation (UVPD) action spectroscopy for the unambiguous identification of peptides associated with the SARS-CoV-2 virus post-digest. Specifically, our analysis will target spike proteins and antibody nucleoproteins to provide additional information with respect to protein sequence and structure. Analysis will include the measurement of peptide wavelength-dependant fragmentation patterns as an additional dimension of unique characterization. The experimental approach will be supplemented by high-level electronic structure theory calculations and resulting data will be used to train predictive machine learning (ML) algorithms for determining peptide and protein structure. This information will be useful for the development of new, fast COVID-19 screening technologies and for the development of vaccines and therapeutics.

该项目涉及滑铁卢大学和质谱仪器公司SCIEX（位于康科德，ON）的研究人员之间的合作。我们建议使用一种组合的方法，包括差分迁移率光谱（DMS），质谱（MS），紫外光解离（UVPD）作用光谱明确识别与SARS-CoV-2病毒消化后的肽。具体而言，我们的分析将针对刺突蛋白和抗体核蛋白，以提供关于蛋白质序列和结构的额外信息。分析将包括肽波长依赖性片段化模式的测量，作为独特表征的额外维度。实验方法将通过高级电子结构理论计算进行补充，所得数据将用于训练预测机器学习（ML）算法，以确定肽和蛋白质结构。这些信息将有助于开发新的快速COVID-19筛查技术以及开发疫苗和治疗方法。