Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation.

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL
Tiancheng Wang, Weijie Zhang, Cancan Fang, Nan Wang, Yue Zhuang, Song Gao
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引用次数: 0

Abstract

Background: A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME).

Objectives: To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME.

Methods: This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics.

Results: A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues.

Conclusion: Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

基于网络药理学和生物信息学验证的人参对结直肠癌肿瘤微环境调控机制研究
背景一项关于人参通过调节肿瘤微环境(TME)治疗结直肠癌(CRC)的生物作用的网络药理学研究:研究人参通过调节肿瘤微环境治疗结直肠癌的潜在作用机制:本研究采用了网络药理学、分子对接技术和生物信息学验证。首先,利用中药系统药理学数据库和分析平台(TCMSP)、中药综合数据库(TCMID)和台湾中药数据库(TCM Database@Taiwan)检索人参的有效成分和相应的靶点。其次,通过Genecards、Therapeutic Target Database (TTD)和Online Mendelian Inheritance in Man (OMIM)检索与CRC相关的靶点。第三,通过基因卡片(GeneCards)和美国国家生物技术信息中心(NCBI)-基因(National Center for Biotechnology Information, NCBI-Gene)筛选出与TME相关的靶点。然后通过维恩图得出人参、CRC和TME的共同靶点。随后,在STRING 11.5数据库中构建了蛋白质-蛋白质相互作用(PPI)网络,并将PPI分析确定的交叉靶标引入Cytoscape 3.8.2软件的cytoHubba插件,根据度值最终确定核心靶标。利用 OmicShare Tools 平台对核心靶标进行了基因本体(GO)富集分析和京都基因组百科全书(KEGG)通路分析。Autodock 和 PyMOL 用于分子对接验证和对接结果的可视化数据分析。最后,我们通过生物信息学中的基因表达谱交互分析(GEPIA)和人类蛋白质图谱(HPA)数据库对核心靶标进行了验证:结果:共发现22种活性成分和202个靶点与CRC的TME密切相关。PPI网络图将SRC、STAT3、PIK3R1、HSP90AA1和AKT1确定为可能的核心靶点。Go富集分析表明,它主要参与T细胞协同刺激、淋巴细胞协同刺激、生长激素反应、蛋白质输入等生物学过程;KEGG通路分析发现了123条相关信号通路,包括表皮生长因子受体酪氨酸激酶抑制剂耐药、趋化因子信号通路、血管内皮生长因子信号通路、ErbB信号通路、PD-L1表达和癌症中的PD-1检查点通路等。分子对接结果表明,人参的主要化学成分与核心靶点具有稳定的结合活性。GEPIA数据库的结果显示,PIK3R1的mRNA水平在CRC组织中明显低表达,而HSP90AA1则明显高表达。对核心靶标 mRNA 水平与 CRC 病理分期关系的分析表明,SRC 的水平随病理分期的变化而明显变化。HPA数据库结果显示,SRC在CRC组织中的表达水平升高,而STAT3、PIK3R1、HSP90AA1和AKT1在CRC组织中的表达水平降低:结论:人参可作用于SRC、STAT3、PIK3R1、HSP90AA1和AKT1,调节T细胞成本刺激、淋巴细胞成本刺激、生长激素反应和蛋白质输入,是调节CRC TME的分子机制。这反映了人参在调节 CRC TME 中的多靶点、多途径作用,为进一步揭示人参的药理基础、作用机制和新药设计开发提供了新思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Current computer-aided drug design
Current computer-aided drug design 医学-计算机:跨学科应用
CiteScore
3.70
自引率
5.90%
发文量
46
审稿时长
>12 weeks
期刊介绍: Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.
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