Identification and functional prediction of new triterpenoids from Alismatis Rhizoma using HPLC-HRMS and in-silico analysis

Abstract

Alismatis Rhizoma (AR) is a crucial substance for discovering new triterpenoids to address hyperlipidemia and obesity. Currently, approximately 120 triterpenoids have been identified in AR, making the discovery of new triterpenoids increasingly challenging. Thus, based on the advantages of HPLC-HRMS, it was utilized to identify both reported and new triterpenoids, and then in-silico analysis was employed to predict the functions of these new triterpenoids. Twenty reported triterpenoids and four new triterpenoids (25-methoxy-16-oxo-11-anhydroalisol A, 25-methoxy-16-oxo-alisol A, 25-methoxy-16-oxo-alisol A 23-acetate, and 25-methoxy-16-oxo-alisol A 24-acetate) from AR were identified using HPLC-HRMS, and then KEGG analysis suggested four new triterpenoids might be activated the PPAR signaling pathway to relieve hyperlipemia. The results of PPI and molecular docking indicated PPARA might be the key targets for anti-hyperlipidemia of four new triterpenoids, of which 25-methoxy-16-oxo-11-anhydroalisol A has better binding activity with PPARA. Additionally, 25-methoxy-16-oxo-11-anhydroalisol A has more potential as a candidate drug because of its better absorption, distribution, metabolism, excretion, and lower toxicity. Hence, our findings proved there are new triterpenoids with anti-hyperlipidemia medicinal potential in AR, thereby guiding the direction of future works and reducing the consumption of time and financial resources.

Keywords

• Alismatis Rhizoma
• HPLC-HRMS
• In-silico analysis
• Molecular docking
• ADMET prediction