Xinjiang Laboratory of Native Medicinal and Edible Plant Resources Chemistry, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China.
Xinjiang Laboratory of Native Medicinal and Edible Plant Resources Chemistry, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2022 Mar 5;268:120601. doi: 10.1016/j.saa.2021.120601. Epub 2021 Nov 11.
α-Glucosidase is one of the main enzymes causing elevated blood glucose, and Coreopsis tinctoria extract can be used as a natural inhibitor of α-Glucosidase. Therefore, a new method was proposed for predicting the inhibitory activity on α-Glucosidase of Coreopsis tinctoria extract based on near infrared spectroscopy. The absorbance of the inhibitory system was measured by ultraviolet spectroscopy, which was used to study the inhibitory activity on a-glucosidase of Coreopsis tinctoria extract. The near infrared spectra of the solid samples were collected. By selecting spectral preprocessing and optimizing spectral bands, a rapid prediction model of the inhibitory activity was established by partial least squares regression. The root mean square error of cross-validation (RMSECV), correlation coefficient (R) value and the ratio of prediction to deviation (RPD) value were used as indicators of the evaluation model. The near infrared spectrum model was established by combining the best spectral preprocessing of the continuous wavelet transform (CWT) and the best spectral band. The root mean square error of cross-validation (RMSECV) of this model was 0.815%, the correlation coefficient (R) value was 0.942, and the ratio of prediction to deviation (RPD) was 3.0. The root mean square error of prediction (RMSEP) of the model by prediction set was 0.819%, the correlation coefficient (R) value was 0.950, and the RPD was 3.2. The model shows that the fitting relationship between the predicted inhibition value and the reference inhibition value of the near infrared spectral model is good. The results showed that there was a good correlation between near infrared spectroscopy and the inhibitory activity of Coreopsis tinctoria extract. Thus, the established model was robust and effective and could be used for rapid quantification of α-Glucosidase inhibitory activity. The prediction method is simple and rapid, and can be extended to study the inhibition of other medicinal plants.
α-葡萄糖苷酶是导致血糖升高的主要酶之一，而金鸡菊提取物可用作α-葡萄糖苷酶的天然抑制剂。因此，提出了一种基于近红外光谱法预测金鸡菊提取物对α-葡萄糖苷酶抑制活性的新方法。采用紫外光谱法测定抑制体系的吸光度，研究金鸡菊提取物对α-葡萄糖苷酶的抑制活性。采集固体样品的近红外光谱，通过选择光谱预处理和优化光谱波段，采用偏最小二乘回归建立抑制活性的快速预测模型。采用交叉验证均方根误差（RMSECV）、相关系数（R）值和预测偏差比（RPD）值作为评价模型的指标。该模型结合连续小波变换（CWT）的最佳光谱预处理和最佳光谱波段建立近红外光谱模型，该模型的交叉验证均方根误差（RMSECV）为 0.815%，相关系数（R）值为 0.942，预测偏差比（RPD）值为 3.0。预测集模型的预测均方根误差（RMSEP）为 0.819%，相关系数（R）值为 0.950，RPD 值为 3.2。模型表明，近红外光谱模型预测抑制值与参考抑制值之间具有良好的拟合关系。结果表明，近红外光谱法与金鸡菊提取物的抑制活性具有良好的相关性。因此，所建立的模型具有良好的稳健性和有效性，可用于快速定量α-葡萄糖苷酶抑制活性。该预测方法简单快速，可扩展用于研究其他药用植物的抑制作用。
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