Meraj Lubna, Mehmood Nasir, Majeed Muhammad Irfan, Nawaz Haq, Rashid Nosheen, Fatima Rida, Habiba Umm E, Tahseen Hira, Naz Maira, Asghar Maria, Ghafoor Nida, Ahmad Hafsa
Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Photodiagnosis Photodyn Ther. 2023 Dec;44:103796. doi: 10.1016/j.pdpdt.2023.103796. Epub 2023 Sep 10.
Insulin storage above the temperature recommended by food and drug administration (FDA) causes decrease in its functional efficacy due to degradation and aggregation of its protein based active pharmaceutical ingredient (API) that results poor glycemic control in diabetic patients. The aggregation of protein causes serious neurodegenerative diseases such as type-2 diabetes, Huntington disease, Parkinson's disease, and Alzheimer's disease. Surface-enhanced Raman spectroscopy (SERS) has been employed for the denaturation study of many proteins at the temperature above the recommendations of food and drug administration (FDA) (above 30 °C) which indicates potential of technique for such studies.
SERS along with multivariate discriminating analysis techniques-based analysis of degradation of liquid pharmaceutical insulin protein after regular intervals of time at room temperature to analyze the structural changes in this protein during the storage of insulin pharmaceutical at room temperature.
Silver nanoparticles (Ag-NPs) prepared by chemical reduction method are used as SERS active substrate for the surface enhancement of the insulin spectral signal. SERS spectral measurements of insulin were collected from eight different samples of insulin in the time range of 7 pm to 7 am first at fridge temperature (5 °C), second after half hour and next six with the time difference of 2 h each time at room temperature. The acquired SERS spectral data was preprocessed and analyzed. SERS structural transformations detection and discrimination potential in insulin was further confirmed by applying multivariate discriminating analysis techniques including principal component analysis (PCA) and Partial least square regression analysis (PLSR).
SERS significantly detects the structural changes produced in insulin even after 2 h of insulin placement at room temperature. PCA successfully differentiates the insulin spectral data obtained after regular intervals of time according to PC-1 (77 %) explained variance. Application of PLSR model provides quantitative confirmation of SERS efficiency, by providing insulin data regression coefficients plot, efficient prediction of time with calibration data set having 0.77 mean square absolute error of calibration (RMSAEC), validation data set with 0.80 mean square absolute error of prediction (RMSAEP) and 0.98 coefficient of determination (R) for both calibration and validation data set.
SERS is proved as a highly sensitive and discriminating technique to detect and discriminate insulin structural changes after regular intervals of time at room temperature.
胰岛素储存在食品药品监督管理局（FDA）推荐的温度之上时，由于其基于蛋白质的活性药物成分（API）发生降解和聚集，导致其功能效力下降，进而使糖尿病患者的血糖控制不佳。蛋白质聚集会引发严重的神经退行性疾病，如2型糖尿病、亨廷顿病、帕金森病和阿尔茨海默病。表面增强拉曼光谱（SERS）已被用于在高于食品药品监督管理局（FDA）建议的温度（30°C以上）下对多种蛋白质进行变性研究，这表明该技术在此类研究中具有潜力。
运用SERS以及基于多变量判别分析技术，对室温下定期放置的液态药用胰岛素蛋白的降解情况进行分析，以研究胰岛素药物在室温储存期间该蛋白的结构变化。
采用化学还原法制备的银纳米颗粒（Ag-NPs）作为SERS活性底物，用于增强胰岛素光谱信号。首先在冷藏温度（5°C）下，于晚上7点至早上7点的时间范围内，从8个不同的胰岛素样品中收集胰岛素的SERS光谱测量数据；其次，半小时后在室温下进行测量，随后每隔2小时测量一次，共测量6次。对采集到的SERS光谱数据进行预处理和分析。通过应用包括主成分分析（PCA）和偏最小二乘回归分析（PLSR）在内的多变量判别分析技术，进一步证实SERS在胰岛素结构转变检测和判别的潜力。
即使在胰岛素于室温放置2小时后，SERS仍能显著检测到胰岛素产生的结构变化。PCA根据PC-1（77%）解释的方差，成功区分了定期采集的胰岛素光谱数据。PLSR模型的应用通过提供胰岛素数据回归系数图，对SERS效率进行了定量确认，校准数据集的平均绝对校准误差（RMSAEC）为0.77，验证数据集的平均绝对预测误差（RMSAEP）为0.80，校准和验证数据集的决定系数（R）均为0.98，从而有效地预测了时间。
事实证明，SERS是一种高度灵敏且具有判别能力的技术，可用于检测和判别室温下定期放置后的胰岛素结构变化。
