Identification of the lipid-lowering component of triterpenes from Alismatis rhizoma based on the MRM-based characteristic chemical profiles and support vector machine model.

Abstract

It has been demonstrated that triterpenes in Alismatis rhizoma (Zexie in Chinese, ZX) contributed to the lipid-lowering effect on high-fat diet-induced hyperlipidemia. Alisol B 23-acetate, one of the abundant triterpenes in ZX, was used as the marker of quality control for ZX in Chinese Pharmacopoeia, while it could not reflect the lipid-lowering effect because other triterpenes in ZX also had prominent medicinal efficacy. To identify the significantly bioactive triterpenes in ZX, a multiple reaction monitoring (MRM)-based characteristic chemical profile (CCP)-support vector machine (SVM) model was used to explore the relationship between triterpenes and lipid-lowering effect of ZX. Firstly, the content of 87 targeted triterpenes was quantified by the MRM-based CCP using UHPLC-QTRAP-MS/MS. Secondly, the lipid-lowering effect of 30 ZX samples was assessed by 3T3-L1 preadipocytes. Thirdly, 9 of the 87 triterpenes possessing high mean impact value were identified to have significant lipid-lowering effect via the particle swarm-optimized SVM model. The new SVM model constructed by the 9 triterpenes showed good prediction performance and the overall prediction accuracy reached 81.94%. Finally, the real activity of these triterpenes was partly confirmed and was consistent with the prediction of SVM. These results showed that the method for discovery of triterpenes with prominent lipid-lowering activity in ZX was reliable. The proposed method is expected to provide an efficient and rapid approach for screening of active component and drug discovery in traditional herbs. Graphical abstract.