Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400044, China.
Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, 200240, China.
J Pharm Biomed Anal. 2021 Feb 5;194:113816. doi: 10.1016/j.jpba.2020.113816. Epub 2020 Dec 5.
Mass spectrometry based precision identification of natural products requires the validation of the reference compounds. This study attempted to develop a LC-QTOF MS combined with LC-TQ MS method to precisely characterize the chemicals of Si-Ni-San (SNS), a classic traditional Chinese medicine formula, which is composed of four medicinal plants, and widely used for the treatments of liver disorders. 74 compounds in SNS were provisionally identified by acquiring MS spectra and MS/MS spectra of the possible chemical features, as well as retrieving small-molecule database. By comparing with the accurate MS/MS spectra of reference compounds, 37 compounds in SNS were precisely identified for the first time. In addition, our effort also successfully assigned the origin of each identified compounds against four medicinal plants. Furthermore, we developed a UHPLC-TQ MS based quantitative-profiling method for simultaneous determination of 37 targeted compounds in the different extracts of the raw SNS and commercial lyophilized powders, enabling to facilitate overall quality control of SNS and associated commercial products. Collectively, our finding precisely characterized the main chemicals in SNS, which also provides a new strategy with LC-MS/MS based chemical profiling to precisely identify a diversity of chemicals in Chinese medicinal plants and associated formulae.
基于质谱的天然产物精确定性需要对参考化合物进行验证。本研究试图开发一种 LC-QTOF MS 与 LC-TQ MS 相结合的方法，以精确表征 Si-Ni-San（SNS）的化学成分，SNS 是一种经典的中药配方，由四种药用植物组成，广泛用于治疗肝脏疾病。通过获取可能的化学特征的 MS 光谱和 MS/MS 光谱，并检索小分子数据库，对 SNS 中的 74 种化合物进行了初步鉴定。通过与参考化合物的精确 MS/MS 光谱进行比较，首次精确鉴定了 SNS 中的 37 种化合物。此外，我们的努力还成功地确定了每种鉴定化合物在四种药用植物中的来源。此外，我们还开发了一种基于 UHPLC-TQ MS 的定量分析方法，用于同时测定原始 SNS 和商业冻干粉末的不同提取物中的 37 种目标化合物，从而便于 SNS 及其相关商业产品的整体质量控制。总的来说，我们的研究结果精确地描述了 SNS 中的主要化学成分，也为基于 LC-MS/MS 的化学特征图谱分析提供了一种新策略，可用于精确鉴定中药植物及其相关配方中的多种化学成分。
