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

该项目涉及滑铁卢大学的研究人员和质谱学仪器公司SCIEX(总部设在安大略省康科德)之间的合作。我们建议使用一种组合方法，包括差示迁移率光谱(DMS)、质谱学(MS)和紫外线光解离(UVPD)作用光谱，用于明确识别与SARS-CoV-2病毒后消化相关的多肽。具体地说，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。分析将包括测量依赖于波长的多肽的碎裂模式，作为独特表征的另一个维度。实验方法将得到高级电子结构理论计算的补充，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新冠肺炎筛查技术以及疫苗和治疗学的开发。

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.