Hypolipidemic and Antithrombotic Effect of 6′-O-Caffeoylarbutin from Vaccinium dunalianum Based on Zebrafish Model, Network Pharmacology, and Molecular Docking

Abstract

Vaccinium dunalianum leaf buds make one of the most commonly used herbal teas of the Yi people in China, which is used to treat articular rheumatism, relax tendons, and stimulates blood circulation in the body. In addition, 6′-O-caffeoylarbutin (CA) is a standardized extract of V. dunalianum, which has been found in dried leaf buds, reaching levels of up to 31.76%. Because of the uncommon phenomenon, it is suggested that CA may have a potential therapeutic role in hyperlipidemia and thrombosis. This study was designed to study the efficacy of CA on treating hyperlipidemia and thrombosis and the possible mechanisms behind these effects. Hyperlipidemia and thrombosis zebrafish models were treated with CA to observe variations of the integrated optical density within the vessels and the intensity of erythrocyte staining within the hearts. The possible mechanisms were explored using network pharmacology and molecular docking. The results demonstrate that CA exhibits an excellent hypolipidemic effect on zebrafish at concentrations ranging from 3.0 to 30.0 μg/mL and shows thrombosis inhibitory activity in zebrafish at a concentration of 30.0 μg/mL, with an inhibition rate of 44%. Moreover, network pharmacological research shows that MMP9, RELA, MMP2, PRKCA, HSP90AA1, and APP are major targets of CA for therapy of hyperlipidemia and thrombosis, and may relate to pathways in cancer, chemical carcinogenesis-receptor activation, estrogen signaling pathway, and the AGE–RAGE signaling pathway in diabetic complications.

Anti-Tumor Activity and Mechanism of Silibinin Based on Network Pharmacology and Experimental Verification

“…Network pharmacology based on gene, protein and disease database information has become an emerging and effective strategy to observe drug action at the organ and organism levels and investigate the pharmacological mechanism of TCMs and their active ingredients [16,17]. This method is used to predict compound-proteins/genes-disease relationships from a network perspective relating to drugs, bioactivity and diseases, and can be applied in different fields such as pharmacological mechanistic studies, drug development and targeted exploration [18,19]. The mechanisms of Tanshinone IIA for treating liver fibrosis were predicted using a network pharmacology approach [20].…”