乌头
化学
乌头碱
色谱法
四极飞行时间
质谱法
传统医学
生物碱
串联质谱法
立体化学
医学
作者
Ashwani Punia,Robin Joshi,Rajiv Kumar
摘要
Abstract Introduction Aconitum spp. are prime medicinal plants rich in alkaloids and have been used as the main constituents of traditional medicine in India and China. The whole plant can be toxic and creates pathophysiological conditions inside the human body. Therefore, simultaneous quantification of alkaloids within plant parts and herbal medicines associated with this genus is essential for quality control. Objective We aimed to develop and validate methods using ultra‐high‐performance liquid chromatography–diode array detector–quadrupole time‐of‐flight ion mobility mass spectrometry (UHPLC‐DAD‐QTOF‐IMS) and to develop an analytical strategy for the identification and quantification of alkaloid compounds (aconitine, hypaconitine, mesaconitine, aconine, benzoylmesaconitine, benzoylaconine, bulleyaconitine A, and deoxyaconitine) from Aconitum heterophyllum . Methodology We developed a simultaneous identification and quantification method for eight alkaloids using UHPLC‐DAD‐QTOF‐IMS. The method was validated as per International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines and also in IMS mode. Results The developed method has good linearity (r 2 = 0.997–0.999), LOD (0.63–8.31 μg/mL), LOQ (0.63–2.80 μg/mL), recovery (86.01–104.33%), reproducibility, intra‐ and inter‐day variability (<3.25%), and stability. Significant qualitative and quantitative variations were found among different plant parts (flower, leaf, stem, root, and tuber) and five market products of A. heterophyllum . Furthermore, a total of 21 metabolites were also profiled based on the fragmentation pattern of MS 2 using the validated method. Conclusion An appropriate mobile phase using acetonitrile and water in a gradient elution gave a satisfactory chromatographic separation of eight Aconitum alkaloids with their adjacent peaks. Therefore, this method could provide a scientific and technical platform for quality control assurance.
科研通智能强力驱动
Strongly Powered by AbleSci AI