Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from Gardenia jasminoides Ellis

被引：2

作者：

Liu, Huining ^{[1
]}

Yu, Shuang ^{[1
]}

Li, Xueyan ^{[1
]}

Wang, Xinyu ^{[1
]}

Qi, Dongying ^{[1
]}

Pan, Fulu ^{[1
]}

Chai, Xiaoyu ^{[1
]}

Wang, Qianqian ^{[1
]}

Pan, Yanli ^{[2
]}

Zhang, Lei ^{[3
]}

Liu, Yang ^{[1
]}

机构：

[1] Beijing Univ Chinese Med, Sch Chinese Mat Med, Beijing 102488, Peoples R China

[2] China Acad Chinese Med Sci, Inst Informat Tradit Chinese Med, Beijing 100700, Peoples R China

[3] Peking Univ Third Hosp, Inst Med Innovat & Res, Beijing 100191, Peoples R China

来源：

MOLECULES | 2023年 / 28卷 / 21期

关键词：

deep-learning model; sequential metabolism; DPP-IV inhibitor; Gardenia jasminoides Ellis; genipin; 1-gentiobioside; THERAPIES; RECEPTOR;

D O I：

10.3390/molecules28217381

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant gap in the exploration of its pharmacologically active components. Integrated strategies encompassing deep-learning prediction models and active validation based on absorbable ingredients can greatly improve the identification rate and screening efficiency in TCM. In this study, the affinity prediction of 11,549 compounds from the traditional Chinese medicine system's pharmacology database (TCMSP) with dipeptidyl peptidase-IV (DPP-IV) based on a deep-learning model was firstly conducted. With the results, Gardenia jasminoides Ellis (GJE), a food medicine with homologous properties, was selected as a model drug. The absorbed components of GJE were subsequently identified through in vivo intestinal perfusion and oral administration. As a result, a total of 38 prototypical absorbed components of GJE were identified. These components were analyzed to determine their absorption patterns after intestinal, hepatic, and systemic metabolism. Virtual docking and DPP-IV enzyme activity experiments were further conducted to validate the inhibitory effects and potential binding sites of the common constituents of deep learning and sequential metabolism. The results showed a significant DPP-IV inhibitory activity (IC50 53 +/- 0.63 mu g/mL) of the iridoid glycosides' potent fractions, which is a novel finding. Genipin 1-gentiobioside was screened as a promising new DPP-IV inhibitor in GJE. These findings highlight the potential of this innovative approach for the rapid screening of active ingredients in TCM and provide insights into the molecular mechanisms underlying the anti-diabetic activity of GJE.

引用

页数：18