An integrated strategy to study the combination mechanisms of Bupleurum chinense DC and Paeonia lactiflora Pall for treating depression based on correlation analysis between serum chemical components profiles and endogenous metabolites profiles

白芍 代谢组学 代谢物 药理学 化学 传统医学 医学 生物化学 色谱法 病理 替代医学
作者
Congcong Chen,Junshen Tian,Xiaoxia Gao,Xuemei Qin,Guanhua Du,Yuzhi Zhou
出处
期刊:Journal of Ethnopharmacology [Elsevier]
卷期号:305: 116068-116068 被引量:9
标识
DOI:10.1016/j.jep.2022.116068
摘要

Bupleurum chinense DC-Paeonia lactiflora Pall (BCD-PLP) is a common clinical herb pair in traditional Chinese medicine (TCM) prescriptions commonly used to treat depression. However, its combination mechanisms with its anti-depressive effects remain highly unclear.Here, an effective strategy has been developed to study the combination mechanisms of Bupleurum chinense DC (BCD) and Paeonia lactiflora Pall (PLP) by integrating serum pharmacochemistry analysis, metabolomics technology, and molecular docking technology.First, the depression model rats were replicated by the chronic unpredictable mild stress (CUMS) procedure, and the difference in the chemical composition in vivo before and after the combination of BCD and PLP was analyzed by integrating background subtraction and multivariate statistical analysis techniques. Then, UPLC/HRMS-based serum metabolomics was performed to analyze the synergistic effect on metabolite regulation before and after the combination of BCD and PLP. Further, the correlation analysis between the differential exogenous chemical components and the differential endogenous metabolites before and after the combination was employed to dissect the combination mechanisms from a global perspective of combining metabolomics and serum pharmacochemistry. Finally, the molecular docking between the differential chemical components and the key metabolic enzymes was applied to verify the regulatory effect of the differential exogenous chemical components on the differential endogenous metabolites.The serum pharmacochemistry analysis results demonstrated that the combination of BCD and PLP could significantly affect the content of 10 components in BCD (including 5 prototype components were significantly decreased and 5 metabolites were significantly increased) and 8 components in PLP (including 4 prototype components and 3 metabolites were significantly increased, 1 metabolite was significantly decreased), which indicated that the combination could enhance BCD prototype components' metabolism and the absorption of the PLP prototype components. Besides, metabolomics results indicated that the BCD-PLP herb pair group significantly reversed more metabolites (8) than BCD and PLP single herb group (5 & 4) and has a stronger regulatory effect on metabolite disorders caused by CUMS. Furthermore, the correlation analysis results suggested that saikogenin F and saikogenin G were significantly positively correlated with the endogenous metabolite itaconate, an endogenous anti-inflammatory metabolite; and benzoic acid was significantly positively correlated with D-serine, an endogenous metabolite with an antidepressant effect. Finally, the molecular docking results further confirmed that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the in vivo concentration of saikogenin F and benzoic acid, which further enhances its anti-inflammatory activity and anti-depressive effect.In this study, an effective strategy has been developed to study the combination mechanisms of BCD and PLP by integrating serum pharmacochemistry analysis, multivariate statistical analysis, metabolomics technology, and molecular docking technology. Based on this strategy, the present study indicated that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the concentration of saikogenin F and benzoic acid in vivo, which further enhances its anti-depressive effect. In short, this strategy will provide a reliable method for elucidating the herb-herb compatibility mechanism of TCM.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
dingning给LZH的求助进行了留言
1秒前
2秒前
欢呼便当发布了新的文献求助10
3秒前
希望天下0贩的0应助KYN采纳,获得10
3秒前
6秒前
6秒前
youjiang发布了新的文献求助10
7秒前
糊涂虫发布了新的文献求助10
8秒前
wangjun完成签到,获得积分10
8秒前
SPQR完成签到,获得积分10
9秒前
哈哈完成签到,获得积分20
9秒前
流星完成签到,获得积分10
10秒前
QC完成签到 ,获得积分10
10秒前
12秒前
sad发布了新的文献求助10
13秒前
凝子老师发布了新的文献求助10
13秒前
13秒前
lucky完成签到,获得积分10
13秒前
又胖了发布了新的文献求助10
14秒前
16秒前
17秒前
18秒前
Wxxxxx完成签到 ,获得积分10
19秒前
超级小飞侠完成签到 ,获得积分10
20秒前
奋斗靖仇完成签到 ,获得积分10
21秒前
小蘑菇应助凝子老师采纳,获得10
21秒前
21秒前
田様应助sad采纳,获得10
22秒前
demotlx发布了新的文献求助10
23秒前
陈老太完成签到 ,获得积分10
23秒前
buno应助又胖了采纳,获得10
24秒前
24秒前
草莓江完成签到 ,获得积分10
29秒前
背后归尘完成签到,获得积分10
30秒前
30秒前
32秒前
32秒前
demotlx完成签到,获得积分10
32秒前
pencil123应助ybmdyr采纳,获得10
33秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
Luis Lacasa - Sobre esto y aquello 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3528035
求助须知:如何正确求助?哪些是违规求助? 3108306
关于积分的说明 9288252
捐赠科研通 2805909
什么是DOI,文献DOI怎么找? 1540220
邀请新用户注册赠送积分活动 716950
科研通“疑难数据库(出版商)”最低求助积分说明 709851