Oxidative stress can lead to various derivatives of the tyrosine residue in peptides and proteins. A typical product is 3-nitro-L-tyrosine residue (Nit), which can affect protein behavior during neurodegenerative processes, such as those associated with Alzheimer's and Parkinson's diseases. Surface enhanced Raman spectroscopy (SERS) is a technique with potential for detecting peptides and their metabolic products at very low concentrations. To explore the applicability to Nit, we use SERS to monitor tyrosine nitration in Met-Enkephalin, rev-Prion protein, and α-synuclein models. Useful nitration indicators were the intensity ratio of two tyrosine marker bands at 825 and 870 cm⁻¹ and a bending vibration of the nitro group. During the SERS measurement, a conversion of nitrotyrosine to azobenzene containing peptides was observed. The interpretation of the spectra has been based on density functional theory (DFT) simulations. The CAM-B3LYP and ωB97XD functionals were found to be most suitable for modeling the measured data. The secondary structure of the α-synuclein models was monitored by electronic and vibrational circular dichroism (ECD and VCD) spectroscopies and modeled by molecular dynamics (MD) simulations. The results suggest that the nitration in these peptides has a limited effect on the secondary structure, but may trigger their aggregation.

氧化应激可导致肽和蛋白质中酪氨酸残基的各种衍生物。典型的产物是 3-硝基-L-酪氨酸残基 (Nit)，它会影响神经退行性过程中的蛋白质行为，例如与阿尔茨海默氏症和帕金森氏病相关的蛋白质行为。表面增强拉曼光谱 (SERS) 是一种具有检测极低浓度肽及其代谢产物潜力的技术。为了探索对 Nit 的适用性，我们使用 SERS 监测 Met-脑啡肽、rev-朊病毒蛋白和 α-突触核蛋白模型中的酪氨酸硝化。有用的硝化指标是 825 和 870 cm ^-1处两个酪氨酸标记带的强度比和硝基的弯曲振动。在 SERS 测量期间，观察到硝基酪氨酸转化为含偶氮苯的肽。光谱的解释基于密度泛函理论 (DFT) 模拟。发现 CAM-B3LYP 和 ωB97XD 泛函最适合对测量数据进行建模。α-突触核蛋白模型的二级结构通过电子和振动圆二色性（ECD 和 VCD）光谱监测，并通过分子动力学 (MD) 模拟进行建模。结果表明，这些肽中的硝化作用对二级结构的影响有限，但可能会引发它们的聚集。