Xueer Zheng , Chao Shi , Ying Xie , Qing Wen , Tongdan Lyu , Hao Li , Zhenru Wang , Minhe Shen , Ying Zhu , Shanming Ruan
{"title":"解毒三根汤抗结直肠癌生物活性成分:天然药物开发的全新综合研究策略","authors":"Xueer Zheng , Chao Shi , Ying Xie , Qing Wen , Tongdan Lyu , Hao Li , Zhenru Wang , Minhe Shen , Ying Zhu , Shanming Ruan","doi":"10.1016/j.phymed.2025.156795","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Jiedu Sangen Decoction (JSD) is widely used in the treatment of colorectal cancer (CRC) patients in southern China due to its good clinical efficacy, but the effective active ingredients are still unknown.</div></div><div><h3>Purpose</h3><div>This study fully explored the bioactive components of JSD based on an innovative and comprehensive research strategy. Using advanced computer technology (e.g., machine learning AHP-SOM algorithm and molecular dynamics simulation) to identify the most promising bioactive components and key targets in JSD, in order to provide new perspectives for the development of natural drugs.</div></div><div><h3>Methods</h3><div>UPLC-MS/MS was used to screen bioactive components in JSD and rat plasma, and network pharmacology analysis combined with machine learning yielded the most promising bioactive components. RNA-seq was used to screen therapeutic targets before and after JSD acted on SW620 cells, and bioinformatics was used to analyze the clinical significance of these key targets. Molecular docking, molecular dynamics simulation, and experiments verified the most promising bioactive components and their therapeutic targets.</div></div><div><h3>Results</h3><div>JSD exhibited a strong pro-apoptotic effect on CRC in <em>vitro</em>. UPLC-MS/MS screened out 18 prototype components and 8 possible metabolites of JSD entering the blood. Network pharmacology combined with machine learning identified the three most promising bioactive components. RNA sequencing and bioinformatics analysis revealed six key targets of JSD against CRC. Molecular docking and molecular dynamics simulations proposed the most promising \"small molecule drug-target protein\" combinations, and SPR and MST demonstrated the direct binding between them: Resveratrol - CA9, Genistein - NOTUM, and Afzelin - DPEP1. Molecular biology experiments found that resveratrol may promote CRC apoptosis through the CA9/PI3K/AKT signaling pathway, and genistein targets NOTUM to downregulate β-catenin expression to inhibit CRC proliferation.</div></div><div><h3>Conclusion</h3><div>It is feasible to develop a novel and comprehensive research strategy to fully explore bioactive components of JSD and provide full support for natural drug development.</div></div>","PeriodicalId":20212,"journal":{"name":"Phytomedicine","volume":"142 ","pages":"Article 156795"},"PeriodicalIF":6.7000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bioactive components of Jiedu Sangen decoction against colorectal cancer: A novel and comprehensive research strategy for natural drug development\",\"authors\":\"Xueer Zheng , Chao Shi , Ying Xie , Qing Wen , Tongdan Lyu , Hao Li , Zhenru Wang , Minhe Shen , Ying Zhu , Shanming Ruan\",\"doi\":\"10.1016/j.phymed.2025.156795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Jiedu Sangen Decoction (JSD) is widely used in the treatment of colorectal cancer (CRC) patients in southern China due to its good clinical efficacy, but the effective active ingredients are still unknown.</div></div><div><h3>Purpose</h3><div>This study fully explored the bioactive components of JSD based on an innovative and comprehensive research strategy. Using advanced computer technology (e.g., machine learning AHP-SOM algorithm and molecular dynamics simulation) to identify the most promising bioactive components and key targets in JSD, in order to provide new perspectives for the development of natural drugs.</div></div><div><h3>Methods</h3><div>UPLC-MS/MS was used to screen bioactive components in JSD and rat plasma, and network pharmacology analysis combined with machine learning yielded the most promising bioactive components. RNA-seq was used to screen therapeutic targets before and after JSD acted on SW620 cells, and bioinformatics was used to analyze the clinical significance of these key targets. Molecular docking, molecular dynamics simulation, and experiments verified the most promising bioactive components and their therapeutic targets.</div></div><div><h3>Results</h3><div>JSD exhibited a strong pro-apoptotic effect on CRC in <em>vitro</em>. UPLC-MS/MS screened out 18 prototype components and 8 possible metabolites of JSD entering the blood. Network pharmacology combined with machine learning identified the three most promising bioactive components. RNA sequencing and bioinformatics analysis revealed six key targets of JSD against CRC. Molecular docking and molecular dynamics simulations proposed the most promising \\\"small molecule drug-target protein\\\" combinations, and SPR and MST demonstrated the direct binding between them: Resveratrol - CA9, Genistein - NOTUM, and Afzelin - DPEP1. Molecular biology experiments found that resveratrol may promote CRC apoptosis through the CA9/PI3K/AKT signaling pathway, and genistein targets NOTUM to downregulate β-catenin expression to inhibit CRC proliferation.</div></div><div><h3>Conclusion</h3><div>It is feasible to develop a novel and comprehensive research strategy to fully explore bioactive components of JSD and provide full support for natural drug development.</div></div>\",\"PeriodicalId\":20212,\"journal\":{\"name\":\"Phytomedicine\",\"volume\":\"142 \",\"pages\":\"Article 156795\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Phytomedicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0944711325004337\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phytomedicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0944711325004337","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
Bioactive components of Jiedu Sangen decoction against colorectal cancer: A novel and comprehensive research strategy for natural drug development
Background
Jiedu Sangen Decoction (JSD) is widely used in the treatment of colorectal cancer (CRC) patients in southern China due to its good clinical efficacy, but the effective active ingredients are still unknown.
Purpose
This study fully explored the bioactive components of JSD based on an innovative and comprehensive research strategy. Using advanced computer technology (e.g., machine learning AHP-SOM algorithm and molecular dynamics simulation) to identify the most promising bioactive components and key targets in JSD, in order to provide new perspectives for the development of natural drugs.
Methods
UPLC-MS/MS was used to screen bioactive components in JSD and rat plasma, and network pharmacology analysis combined with machine learning yielded the most promising bioactive components. RNA-seq was used to screen therapeutic targets before and after JSD acted on SW620 cells, and bioinformatics was used to analyze the clinical significance of these key targets. Molecular docking, molecular dynamics simulation, and experiments verified the most promising bioactive components and their therapeutic targets.
Results
JSD exhibited a strong pro-apoptotic effect on CRC in vitro. UPLC-MS/MS screened out 18 prototype components and 8 possible metabolites of JSD entering the blood. Network pharmacology combined with machine learning identified the three most promising bioactive components. RNA sequencing and bioinformatics analysis revealed six key targets of JSD against CRC. Molecular docking and molecular dynamics simulations proposed the most promising "small molecule drug-target protein" combinations, and SPR and MST demonstrated the direct binding between them: Resveratrol - CA9, Genistein - NOTUM, and Afzelin - DPEP1. Molecular biology experiments found that resveratrol may promote CRC apoptosis through the CA9/PI3K/AKT signaling pathway, and genistein targets NOTUM to downregulate β-catenin expression to inhibit CRC proliferation.
Conclusion
It is feasible to develop a novel and comprehensive research strategy to fully explore bioactive components of JSD and provide full support for natural drug development.
期刊介绍:
Phytomedicine is a therapy-oriented journal that publishes innovative studies on the efficacy, safety, quality, and mechanisms of action of specified plant extracts, phytopharmaceuticals, and their isolated constituents. This includes clinical, pharmacological, pharmacokinetic, and toxicological studies of herbal medicinal products, preparations, and purified compounds with defined and consistent quality, ensuring reproducible pharmacological activity. Founded in 1994, Phytomedicine aims to focus and stimulate research in this field and establish internationally accepted scientific standards for pharmacological studies, proof of clinical efficacy, and safety of phytomedicines.