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一种采用行波离子迁移率质谱法和分子网络对龟龄集进行结构表征的综合方法。

An integrated approach for structural characterization of Gui Ling Ji by traveling wave ion mobility mass spectrometry and molecular network.

作者信息

Zhang Yuhao, Lei Huibo, Tao Jianfei, Yuan Wenlin, Zhang Weidong, Ye Ji

机构信息

Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine Shanghai 201203 China

College of Pharmacy, The Second Military Medical University Shanghai 200433 China

出版信息

RSC Adv. 2021 Apr 27;11(26):15546-15556. doi: 10.1039/d1ra01834e. eCollection 2021 Apr 26.

Abstract

Gui Ling Ji (GLJ), an ancient reputable traditional Chinese medicine (TCM) formula prescription, has been applied for the treatment of oligospermia and asthenospermia in clinical practice. However, its inherent compounds have not yet been systematically elucidated, which hampers developing standards or guidelines for quality evaluation and even the understanding of pharmacological effects. In this study, an integrated approach has been established for comprehensive structural characterization of GLJ. Mass spectrometry datasets of GLJ and each of the single herb medicines in this prescription have been developed by dynamic exclusion fast data-dependent acquisition and high-definition data-independent acquisition modes on ultra-high-performance liquid chromatography coupled with travelling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS). A global natural product social molecular networking (GNPS) platform was then applied for the visualization of chemical space of GLJ and further for the high throughput identification of the targeted or untargeted compounds due to the support of data-transmitting from each single herbal medicine to the formula GLJ. Moreover, drift time, predicted CCS, and diagnostic fragment ions were induced for annotating isomer compounds. Consequently, based on molecular network and library hits, a total of 257 compounds from GLJ, which were classified into 4 structural types, were positively or tentatively characterized. Among them, 20 potential new compounds were detected and 30 pairs of isomers were comprehensively distinguished. The established strategy was effective for attribution, classification, recognition of various constituents, and also was valuable for integrating large amounts of disordered MS/MS data and mining trace compounds in other complex chemical or biochemical systems.

摘要

龟龄集(GLJ)是一种古老且著名的中药配方,在临床实践中已被用于治疗少精子症和弱精子症。然而,其内在的化合物尚未得到系统阐明,这阻碍了质量评估标准或指南的制定,甚至妨碍了对药理作用的理解。在本研究中,已建立了一种综合方法用于龟龄集的全面结构表征。通过在超高效液相色谱-行波离子淌度四极杆飞行时间质谱(UPLC-TWIMS-QTOF-MS)上采用动态排除快速数据依赖采集和高清数据独立采集模式,生成了龟龄集及其该配方中每种单味中药的质谱数据集。然后应用全球天然产物社会分子网络(GNPS)平台对龟龄集的化学空间进行可视化,并进一步用于高通量鉴定目标或非目标化合物,这得益于从每种单味草药到配方龟龄集的数据传输支持。此外,引入漂移时间、预测的碰撞截面积(CCS)和诊断性碎片离子用于注释同分异构体化合物。结果,基于分子网络和库匹配,共对龟龄集中257种化合物进行了阳性或初步表征,这些化合物分为4种结构类型。其中,检测到20种潜在新化合物,并全面区分了30对同分异构体。所建立的策略对于各种成分的归属、分类、识别是有效的,对于整合大量无序的MS/MS数据以及在其他复杂化学或生化系统中挖掘痕量化合物也具有重要价值。

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