Understanding the Excitation Wavelength Dependence and Thermal Stability of the SARS-CoV-2 Receptor-Binding Domain Using Surface-Enhanced Raman Scattering and Machine Learning
Understanding the Excitation Wavelength Dependence and Thermal Stability of the SARS-CoV-2 Receptor-Binding Domain Using Surface-Enhanced Raman Scattering and Machine Learning
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DOI：
10.1021/acsphotonics.2c00456
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发表时间：
2022-08
期刊：
影响因子：
7
通讯作者：
Kunyan Zhang;Ziyang Wang;He Liu;N. Peréa-López;Jeewan C Ranasinghe;G. Bepete;Allen M. Minns;
中科院分区：
文献类型：
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作者：
Kunyan Zhang;Ziyang Wang;He Liu;N. Peréa-López;Jeewan C Ranasinghe;G. Bepete;Allen M. Minns;
COVID-19 已导致全球数百万人丧生。 SARS-CoV-2 的持续突变需要进行深入研究，以促进变异监测的发展。在这项工作中，我们研究了与 SARS-CoV-2 刺突蛋白（病毒感染的关键成分）受体结合域 (RBD) 的光学识别相关的基本特性。使用金纳米颗粒 (AuNP) 的表面增强拉曼光谱 (SERS) 捕获 SARS-CoV-2 RBD 的拉曼模式。由于 AuNP 聚集，观察到的拉曼增强强烈依赖于激发波长。通过主成分分析对 SARS-CoV-2 和 MERS-CoV 的 RBD 的特征拉曼光谱进行了分析，揭示了二级结构在 SERS 过程中的作用，这与激光加热下的热稳定性得到了证实。我们可以使用机器学习算法轻松区分两个 RBD 的拉曼光谱，准确度、精确度、召回率和 F1 分数均超过 95%。我们的工作提供了对 SARS-CoV-2 RBD 的深入了解，并为快速分析和区分传染性病毒和其他生物分子的复杂蛋白质铺平了道路。
COVID-19 has cost millions of lives worldwide. The constant mutation of SARS-CoV-2 calls for thorough research to facilitate the development of variant surveillance. In this work, we studied the fundamental properties related to the optical identification of the receptor-binding domain (RBD) of SARS-CoV-2 spike protein, a key component of viral infection. The Raman modes of the SARS-CoV-2 RBD were captured by surface-enhanced Raman spectroscopy (SERS) using gold nanoparticles (AuNPs). The observed Raman enhancement strongly depends on the excitation wavelength as a result of the aggregation of AuNPs. The characteristic Raman spectra of RBDs from SARS-CoV-2 and MERS-CoV were analyzed by principal component analysis that reveals the role of secondary structures in the SERS process, which is corroborated with the thermal stability under laser heating. We can easily distinguish the Raman spectra of two RBDs using machine learning algorithms with accuracy, precision, recall, and F1 scores all over 95%. Our work provides an in-depth understanding of the SARS-CoV-2 RBD and paves the way toward rapid analysis and discrimination of complex proteins of infectious viruses and other biomolecules.