Faculty of Pharmacy, International Islamic University, Kuantan Campus, Pahang, Malaysia.
Department of Food Science and Nutrition, King Saud University, Riyadh, Saudi Arabia.
J Food Drug Anal. 2017 Apr;25(2):306-315. doi: 10.1016/j.jfda.2016.09.007. Epub 2016 Nov 5.
Phaleria macrocarpa, known as "Mahkota Dewa", is a widely used medicinal plant in Malaysia. This study focused on the characterization of α-glucosidase inhibitory activity of P. macrocarpa extracts using Fourier transform infrared spectroscopy (FTIR)-based metabolomics. P. macrocarpa and its extracts contain thousands of compounds having synergistic effect. Generally, their variability exists, and there are many active components in meager amounts. Thus, the conventional measurement methods of a single component for the quality control are time consuming, laborious, expensive, and unreliable. It is of great interest to develop a rapid prediction method for herbal quality control to investigate the α-glucosidase inhibitory activity of P. macrocarpa by multicomponent analyses. In this study, a rapid and simple analytical method was developed using FTIR spectroscopy-based fingerprinting. A total of 36 extracts of different ethanol concentrations were prepared and tested on inhibitory potential and fingerprinted using FTIR spectroscopy, coupled with chemometrics of orthogonal partial least square (OPLS) at the 4000-400 cm frequency region and resolution of 4 cm. The OPLS model generated the highest regression coefficient with RY = 0.98 and QY = 0.70, lowest root mean square error estimation = 17.17, and root mean square error of cross validation = 57.29. A five-component (1+4+0) predictive model was build up to correlate FTIR spectra with activity, and the responsible functional groups, such as -CH, -NH, -COOH, and -OH, were identified for the bioactivity. A successful multivariate model was constructed using FTIR-attenuated total reflection as a simple and rapid technique to predict the inhibitory activity.
皱籽榕,俗称“帝王果”,是马来西亚广泛使用的药用植物。本研究采用基于傅里叶变换红外光谱(FTIR)的代谢组学方法,对皱籽榕提取物的α-葡萄糖苷酶抑制活性进行了表征。皱籽榕及其提取物含有数千种具有协同作用的化合物。一般来说,它们的变异性存在,而且有许多活性成分含量很少。因此,传统的单一成分质量控制测量方法既耗时、费力、昂贵又不可靠。因此,开发一种快速的草药质量控制预测方法来研究皱籽榕的α-葡萄糖苷酶抑制活性,通过多组分分析来研究皱籽榕的α-葡萄糖苷酶抑制活性,具有重要意义。在本研究中,采用基于 FTIR 光谱的指纹图谱法,建立了一种快速简单的分析方法。共制备了 36 种不同乙醇浓度的提取物,测定其抑制潜力,并采用 FTIR 光谱进行指纹图谱分析,同时结合正交偏最小二乘法(OPLS)化学计量学在 4000-400 cm 频率区域和 4 cm 分辨率下进行分析。OPLS 模型生成的回归系数最高,RY=0.98,QY=0.70,均方根误差估计值最低,为 17.17,交叉验证均方根误差为 57.29。建立了一个五组分(1+4+0)预测模型,将 FTIR 光谱与活性相关联,并确定了负责的功能基团,如-CH、-NH、-COOH 和-OH,用于生物活性。使用 FTIR-衰减全反射建立了一个成功的多元模型,作为一种简单快速的技术来预测抑制活性。