The inhibition mechanisms of pancreatic lipase by apigenin and its anti-obesity mechanisms revealed by using network pharmacology

芹菜素 化学 小桶 生物化学 药理学 对接(动物) 黄酮类 PI3K/AKT/mTOR通路 信号转导 基因 生物 类黄酮 医学 基因本体论 基因表达 抗氧化剂 护理部 色谱法
作者
Fuqiang Liang,Yumeng Shi,Weiwei Cao,Jiayi Shi
出处
期刊:Food bioscience [Elsevier BV]
卷期号:45: 101515-101515 被引量:14
标识
DOI:10.1016/j.fbio.2021.101515
摘要

This study aimed to elucidate the inhibition mechanism of apigenin against porcine pancreatic lipase (PPL), and, moreover, to comprehensively reveal the molecular basis of its anti-obesity via network pharmacology approach. The results showed that apigenin inhibited PPL with an IC50 value of 0.377 ± 0.041 mM. Spectroscopic techniques combined molecular docking suggested that apigenin could bind into the PPL active pocket, affecting its normal spatial conformation. Moreover, molecular dynamic (MD) simulations revealed that the open conformation of PPL tended to transit to the closed in the presence of apigenin, which might one important reason for the inhibition of PPL catalytic ability. Network pharmacology analysis revealed that a total of 49 proteins could be identified as potential targets for the anti-obesity effects of apigenin. According to the protein-protein interaction (PPI) network analysis, six hub targets were extracted including IGF1, ESR1, MMP9, PPARA, MAPK14 and NR3C1. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicated that the 49 potential targets could be mapped to 30 pathways (p<0.05). Among them, PI3K-Akt signaling pathway and insulin resistance can be considered as two major pathways regulated by apigenin. Further docking studies indicated that apigenin can bind into the binding pocket of the six hub target proteins identified according to the PPI network. The results indicated that in addition to inhibiting PPL, apigenin could exhibit anti-obesity benefit through the molecular mechanisms uncovered by network pharmacology. This study proposes a new strategy to reveal the mechanisms of dietary polyphenols at the level of network pharmacology.
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