Predicting the Mechanism of Tiannanxing-shengjiang Drug Pair in Treating Pain Using Network Pharmacology and Molecular Docking Technology

机制(生物学) 计算生物学 生物 对接(动物) 药理学 药品 化学 医学 认识论 哲学 护理部
作者
Boning Wang,Yanlei Wang,Peng Mao,Yi Zhang,Yifan Li,Xing Liu,Bifa Fan
出处
期刊:Current Computer - Aided Drug Design [Bentham Science Publishers]
卷期号:20 (5): 463-473
标识
DOI:10.2174/1573409919666230525122447
摘要

Objective: This study aimed to analyze the potential targets and mechanism of the Tiannanxing-shengjiang drug pair in pain treatment using network pharmacology and molecular docking technology. Methods: The active components and target proteins of Tiannanxing-Shengjiang were obtained from the TCMSP database. The pain-related genes were acquired from the DisGeNET database. The common target genes between Tiannanxing-Shengjiang and pain were identified and subjected to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses on the DAVID website. AutoDockTools and molecular dynamics simulation analysis were used to assess the binding of the components with the target proteins. Results: Ten active components were screened out, such as stigmasterol, β-sitosterol, and dihydrocapsaicin. A total of 63 common targets between the drug and pain were identified. GO analysis showed the targets to be mainly associated with biological processes, such as inflammatory response and forward regulation of the EKR1 and EKR2 cascade. KEGG analysis revealed 53 enriched pathways, including pain-related calcium signaling, cholinergic synaptic signaling, and serotonergic pathway. Five compounds and 7 target proteins showed good binding affinities. These data suggest that Tiannanxing-shengjiang may alleviate pain through specific targets and signaling pathways. Conclusion: The active ingredients in Tiannanxing-shengjiang might alleviate pain by regulating genes, such as CNR1, ESR1, MAPK3, CYP3A4, JUN, and HDAC1 through the signaling pathways, including intracellular calcium ion conduction, cholinergic prominent signaling, and cancer signaling pathway.

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
十七完成签到 ,获得积分10
1秒前
cicy完成签到,获得积分10
1秒前
慕容飞凤完成签到,获得积分10
3秒前
李大姐完成签到,获得积分20
3秒前
小石榴的爸爸完成签到 ,获得积分10
11秒前
Chris完成签到 ,获得积分10
12秒前
14秒前
anzhe完成签到,获得积分10
15秒前
小石榴爸爸完成签到 ,获得积分10
18秒前
dao发布了新的文献求助10
19秒前
梓树完成签到,获得积分10
20秒前
zybbb完成签到 ,获得积分10
21秒前
123关闭了123文献求助
23秒前
123驳回了慕青应助
27秒前
木子木子粒完成签到 ,获得积分10
27秒前
2385697574完成签到,获得积分10
32秒前
manmanzhong完成签到 ,获得积分10
38秒前
NIHAO完成签到 ,获得积分10
38秒前
tigger完成签到,获得积分10
39秒前
聪慧的迎夏完成签到,获得积分10
43秒前
风趣的小松鼠完成签到 ,获得积分10
43秒前
44秒前
追风少年完成签到,获得积分10
47秒前
冷静的振家完成签到,获得积分10
47秒前
大力的灵雁应助ggjy采纳,获得10
50秒前
嘟嘟豆806完成签到 ,获得积分0
52秒前
54秒前
ycd完成签到,获得积分10
55秒前
58秒前
yunfan完成签到,获得积分10
58秒前
luobote完成签到 ,获得积分10
59秒前
Mason完成签到,获得积分10
59秒前
123发布了新的文献求助10
59秒前
hi_traffic完成签到,获得积分10
1分钟前
小东东发布了新的文献求助10
1分钟前
Lzh完成签到 ,获得积分10
1分钟前
iuhgnor完成签到,获得积分0
1分钟前
兰先生完成签到,获得积分20
1分钟前
Laity完成签到,获得积分10
1分钟前
闫栋完成签到 ,获得积分0
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
T/SNFSOC 0002—2025 独居石精矿碱法冶炼工艺技术标准 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6043130
求助须知:如何正确求助?哪些是违规求助? 7802865
关于积分的说明 16237978
捐赠科研通 5188629
什么是DOI,文献DOI怎么找? 2776648
邀请新用户注册赠送积分活动 1759700
关于科研通互助平台的介绍 1643239