Complexity and diversity of natural compounds make it a challenge for globally profiling constituents in multiple species plants, especially for minor new compounds. Rubiaceae-type cyclopeptides (RAs) are one kind of active constituents and characteristic components in Rubia plants, particularly Rubia cordifolia (RC), which is one kind of traditional Chinese medicines. In this study, a new multiple reaction monitoring strategy (PPCP-MRM) based on predicted precursor ions and characteristic product ions was developed to globally profile RAs in RC and its two main adulterants, including Rubia alata (also named Jinjiancao in Chinese) (RAJ) and Rubia podantha (RP). Moreover, characteristic components of these species have been found by targeted relative quantitative analysis of RAs by LC-MS. In total, 39 RAs have been structurally annotated based on fragment ions in MS2 data, including 19 new compounds. In addition, 7 RAs as the chemical markers were found to distinguish these three Rubia species. The results indicated that this PPCP-MRM integrated strategy is a powerful tool for comprehensive analysis of RAs and screening chemical markers for Rubia species discrimination, which would be useful for distinguishing Rubia adulterants. Furthermore, this developed strategy could also be a useful tool for analysis of other cyclopeptides.

中文翻译：

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基于预测的前体离子和特征性产物离子的综合多反应监测策略，用于在三个茜草科物种中进行全球概况的茜草科类环肽分析。

天然化合物的复杂性和多样性使得对多种物种植物中的成分进行全球概况分析尤其是对次要的新化合物而言，这是一个挑战。茜草科类环肽（RAs）是茜草植物中的一种活性成分和特征性成分，尤其是作为一种中药的茜草（RCia）。在这项研究中，开发了一种基于预测的前体离子和特征性产物离子的新的多反应监测策略（PPCP-MRM），以对RC中的RA及其两个主要掺杂物（包括Rubia alata（中文也称为Jinjiancao））进行全球分布）和Rubia podantha（RP）。而且，通过LC-MS对RA进行有针对性的相对定量分析，已经发现了这些物种的特征成分。总共，根据MS2数据中的碎片离子，对39种RA进行了结构注释，包括19种新化合物。此外，发现了7种RA作为化学标记，可以区分这3种茜草属。结果表明，这种PPCP-MRM整合策略是对RA进行综合分析和筛选用于鉴定茜草属种的化学标记的有力工具，这将有助于区分茜草属掺假物。此外，这种开发的策略也可能是分析其他环肽的有用工具。结果表明，这种PPCP-MRM整合策略是对RA进行综合分析和筛选用于鉴定茜草属种的化学标记的有力工具，这将有助于区分茜草属掺假物。此外，这种开发的策略也可能是分析其他环肽的有用工具。结果表明，这种PPCP-MRM整合策略是对RA进行综合分析和筛选用于鉴定茜草属种的化学标记的有力工具，这将有助于区分茜草属掺假物。此外，这种开发的策略也可能是分析其他环肽的有用工具。