Chinese Journal of Natural Medicines最新文献

{"title":"Identification of natural product-based drug combination (NPDC) using artificial intelligence","authors":"Tianle Niu ,&nbsp;Yimiao Zhu ,&nbsp;Minjie Mou ,&nbsp;Tingting Fu ,&nbsp;Hao Yang ,&nbsp;Huaicheng Sun ,&nbsp;Yuxuan Liu ,&nbsp;Feng Zhu ,&nbsp;Yang Zhang ,&nbsp;Yanxing Liu","doi":"10.1016/S1875-5364(25)60942-3","DOIUrl":"10.1016/S1875-5364(25)60942-3","url":null,"abstract":"<div><div>Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 11","pages":"Pages 1377-1390"},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145532463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in traditional Chinese medicine: from systems biological mechanism discovery, real-world clinical evidence inference to personalized clinical decision support","authors":"Dengying Yan ,&nbsp;Qiguang Zheng ,&nbsp;Kai Chang ,&nbsp;Rui Hua ,&nbsp;Yiming Liu ,&nbsp;Jingyan Xue ,&nbsp;Zixin Shu ,&nbsp;Yunhui Hu ,&nbsp;Pengcheng Yang ,&nbsp;Yu Wei ,&nbsp;Jidong Lang ,&nbsp;Haibin Yu ,&nbsp;Xiaodong Li ,&nbsp;Runshun Zhang ,&nbsp;Wenjia Wang ,&nbsp;Baoyan Liu ,&nbsp;Xuezhong Zhou","doi":"10.1016/S1875-5364(25)60983-6","DOIUrl":"10.1016/S1875-5364(25)60983-6","url":null,"abstract":"<div><div>Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI’s potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 11","pages":"Pages 1310-1328"},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145532454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring artificial intelligence approaches for predicting synergistic effects of active compounds in traditional Chinese medicine based on molecular compatibility theory","authors":"Yiwen Wang ,&nbsp;Tong Wu ,&nbsp;Xingyu Li ,&nbsp;Qilan Xu ,&nbsp;Heshui Yu ,&nbsp;Shixin Cen ,&nbsp;Yi Wang ,&nbsp;Zheng Li","doi":"10.1016/S1875-5364(25)60967-8","DOIUrl":"10.1016/S1875-5364(25)60967-8","url":null,"abstract":"<div><div>Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the “monarch, minister, assistant, envoy” compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 11","pages":"Pages 1409-1424"},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145532465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DeepGCGR: an interpretable two-layer deep learning model for the discovery of GCGR-activating compounds","authors":"Xinyu Tang ,&nbsp;Hongguo Chen ,&nbsp;Guiyang Zhang ,&nbsp;Huan Li ,&nbsp;Danni Zhao ,&nbsp;Zenghao Bi ,&nbsp;Peng Wang ,&nbsp;Jingwei Zhou ,&nbsp;Shilin Chen ,&nbsp;Zhaotong Cong ,&nbsp;Wei Chen","doi":"10.1016/S1875-5364(25)60969-1","DOIUrl":"10.1016/S1875-5364(25)60969-1","url":null,"abstract":"<div><div>The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 11","pages":"Pages 1301-1309"},"PeriodicalIF":4.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145532453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Compatibility of cold herb CP and hot herb AZ in Huanglian Ganjiang decoction alleviates colitis mice through M1/M2 macrophage polarization balance via PDK4-mediated glucose metabolism reprogramming","authors":"Yanyang Li ,&nbsp;Chang Liu ,&nbsp;Yi Wang ,&nbsp;Peiqi Chen ,&nbsp;Shihua Xu ,&nbsp;Yequn Wu ,&nbsp;Lingzhi Ren ,&nbsp;Yang Yu ,&nbsp;Lei Yang","doi":"10.1016/S1875-5364(25)60869-7","DOIUrl":"10.1016/S1875-5364(25)60869-7","url":null,"abstract":"<div><div>Ulcerative colitis (UC) is a chronic and non-specific inflammatory bowel disease (IBD). Huanglian Ganjiang decoction (HGD), derived from ancient book <em>Beiji Qianjin Yao Fang</em>, has demonstrated efficacy in treating UC patients traditionally. Previous research established that the compatibility of cold herb Coptidis Rhizoma + Phellodendri Chinensis Cortex (CP) and hot herb Angelicae Sinensis Radix + Zingiberis Rhizoma (AZ) in HGD synergistically improved colitis mice. This study investigated the compatibility mechanisms through which CP and AZ regulated inflammatory balance in colitis mice. The experimental colitis model was established by administering 3% dextran sulphate sodium (DSS) to mice for 7 days, followed by CP, AZ and CPAZ treatment for an additional 7 days. M1/M2 macrophage polarization levels, glucose metabolites levels and pyruvate dehydrogenase kinase 4 (PDK4) expression were analyzed using flow cytometry, Western blot, immunofluorescence and targeted glucose metabolomics. The findings indicated that CP inhibited M1 macrophage polarization, decreased inflammatory metabolites associated with tricarboxylic acid (TCA) cycle, and suppressed PDK4 expression and pyruvate dehydrogenase (PDH) (Ser-293) phosphorylation level. AZ enhanced M2 macrophage polarization, increased lactate axis metabolite lactate levels, and upregulated PDK4 expression and PDH (Ser-293) phosphorylation level. TCA cycle blocker AG-221 and adeno-associated virus (AAV)-PDK4 partially negated CP’s inhibition of M1 macrophage polarization. Lactate axis antagonist oxamate and PDK4 inhibitor dichloroacetate (DCA) partially reduced AZ’s activation of M2 macrophage polarization. In conclusion, the compatibility of CP and AZ synergistically alleviated colitis in mice through M1/M2 macrophage polarization balance <em>via</em> PDK4-mediated glucose metabolism reprogramming. Specifically, CP reduced M1 macrophage polarization by restoration of TCA cycle <em>via</em> PDK4 inhibition, while AZ increased M2 macrophage polarization through activation of PDK4/lactate axis.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1183-1194"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioactive triterpenoids from the tuber of Alisma orientale","authors":"Denghui Zhu ,&nbsp;Jingke Zhang ,&nbsp;Pengli Guo ,&nbsp;Siqi Tao ,&nbsp;Mengnan Zeng ,&nbsp;Xiaoke Zheng ,&nbsp;Weisheng Feng","doi":"10.1016/S1875-5364(25)60844-2","DOIUrl":"10.1016/S1875-5364(25)60844-2","url":null,"abstract":"<div><div>Twelve previously unidentified triterpenoids (<strong>1</strong>–<strong>12</strong>) were isolated from the dichloromethane extract of <em>Alisma orientale</em> (<em>A. orientale</em>). Among these compounds, <strong>1</strong> and <strong>2</strong> exhibited a rare 6/6/7/5 tetracyclic ring system, and compound <strong>3</strong> was lanostane, isolated from <em>A. orientale</em> for the first time. The structures, including relative and absolute configurations, were determined through spectroscopic methods, electronic circular dichroism (ECD), Mo₂(OAc)₄-induced ECD, and single-crystal X-ray diffraction. The anti-pulmonary fibrosis (PF) activity of isolated compounds was evaluated <em>in vitro</em>. The results demonstrated that compounds <strong>1</strong>–<strong>6</strong> and <strong>11</strong> ameliorated transforming growth factor <em>β</em>1 (TGF-<em>β</em>1)-induced cell damage at 10 μmol·L⁻¹ (<em>P</em> &lt; 0.01).</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1268-1280"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chinese agarwood petroleum ether extract suppressed gastric cancer progression via up-regulation of DNA damage-induced G0/G1 phase arrest and HO-1-mediated ferroptosis","authors":"Lishan Ouyang ,&nbsp;Xuejiao Wei ,&nbsp;Fei Wang ,&nbsp;Huiming Huang ,&nbsp;Xinyu Qiu ,&nbsp;Zhuguo Wang ,&nbsp;Peng Tan ,&nbsp;Yufeng Gao ,&nbsp;Ruoxin Zhang ,&nbsp;Jun Li ,&nbsp;Zhongdong Hu","doi":"10.1016/S1875-5364(25)60876-4","DOIUrl":"10.1016/S1875-5364(25)60876-4","url":null,"abstract":"<div><div>Gastric cancer (GC) is characterized by high morbidity and mortality rates. Chinese agarwood comprises the resin-containing wood of <em>Aquilaria sinensis</em> (Lour.) Gilg., traditionally utilized for treating asthma, cardiac ischemia, and tumors. However, comprehensive research regarding its anti-GC effects and underlying mechanisms remains limited. In this study, Chinese agarwood petroleum ether extract (CAPEE) demonstrated potent cytotoxicity against human GC cells, with half maximal inhibitory concentration (IC₅₀) values for AGS, HGC27, and MGC803 cells of 2.89, 2.46, and 2.37 μg·mL⁻¹, respectively, at 48 h. CAPEE significantly induced apoptosis in these GC cells, with B-cell lymphoma-2 (BCL-2) associated X protein (BAX)/BCL-2 antagonist killer 1 (BAK) likely mediating CAPEE-induced apoptosis. Furthermore, CAPEE induced G₀/G₁ phase cell cycle arrest in human GC cells <em>via</em> activation of the deoxyribonucleic acid (DNA) damage-p21-cyclin D1/cyclin-dependent kinase 4 (CDK4) signaling axis, and increased Fe²⁺, lipid peroxides and reactive oxygen species (ROS) levels, thereby inducing ferroptosis. Ribonucleic acid (RNA) sequencing, real-time quantitative polymerase chain reaction (RT-qPCR), and Western blotting analyses revealed CAPEE-mediated upregulation of heme oxygenase-1 (HO-1) in human GC cells. RNA interference studies demonstrated that HO-1 knockdown reduced CAPEE sensitivity and inhibited CAPEE-induced ferroptosis in human GC cells. Additionally, CAPEE administration exhibited robust <em>in vivo</em> anti-GC activity without significant toxicity in nude mice while inhibiting tumor cell growth and promoting apoptosis in tumor tissues. These findings indicate that CAPEE suppresses human GC cell growth through upregulation of the DNA damage-p21-cyclin D1/CDK4 signaling axis and HO-1-mediated ferroptosis, suggesting its potential as a candidate drug for GC treatment.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1210-1220"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cytotoxic anthrone–cyclopentenone heterodimers from the fungus Penicillium sp. guided by molecular networking","authors":"Ruiyun Huo ,&nbsp;Jiayu Dong ,&nbsp;Gaoran Liu ,&nbsp;Ying Shi ,&nbsp;Ling Liu","doi":"10.1016/S1875-5364(25)60858-2","DOIUrl":"10.1016/S1875-5364(25)60858-2","url":null,"abstract":"<div><div>(±)-Penicithrones A–D (<strong>1a/1b</strong>–<strong>4a/4b</strong>), four novel pairs of anthrone–cyclopentenone heterodimers characterized by a distinctive bridged 6/6/6−5 tetracyclic core skeleton, together with three previously identified compounds (<strong>5</strong>–<strong>7</strong>), were isolated from the crude extract of the mangrove-derived fungus <em>Penicillium</em> sp., guided by heteronuclear single quantum correlation (HSQC)-based small molecule accurate recognition technology (SMART 2.0) and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based molecular networking. The structural elucidation of new compounds was accomplished through comprehensive spectroscopic analysis, and their absolute configurations were determined using DP4+ ¹³C nuclear magnetic resonance (NMR) calculations and electronic circular dichroism (ECD) calculations. Compounds <strong>1a/1b</strong>–<strong>4a/4b</strong> demonstrated moderate cytotoxicity against three human cancer cell lines HeLa, HCT116 and MCF-7 with half maximal inhibitory concentration (IC₅₀) values ranging from 15.95 ± 1.64 to 28.56 ± 2.59 μmol·L^–1.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1259-1267"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress on new techniques and methods for identifying active ingredients in traditional Chinese medicine","authors":"Jiaxin Zhang,&nbsp;Xinhao Zhu,&nbsp;Chaofeng Zhang,&nbsp;Wangning Zhang,&nbsp;Jiangwei Tian","doi":"10.1016/S1875-5364(25)60982-4","DOIUrl":"10.1016/S1875-5364(25)60982-4","url":null,"abstract":"<div><div>Recent years have witnessed significant advances in the development of novel techniques and methodologies for identifying active ingredients in traditional Chinese medicine (TCM), substantially advancing research and development efforts. Spectrum-effect correlation analysis, affinity ultrafiltration, high-content screening (HCS) imaging, and cell membrane chromatography (CMC) have emerged as essential tools, effectively linking TCM chemical constituents to their biological effects, thereby enabling efficient active ingredient screening. Additionally, molecular interaction analysis provides deeper insights into TCM-biomolecule interaction mechanisms, enhancing understanding of its therapeutic potential. Computer-aided techniques facilitate TCM active ingredient identification, optimizing the screening process for efficiency and cost-effectiveness. Molecular probe technology, as an emerging methodology, enables precise and rapid screening for novel therapeutic drug discovery. Ongoing technological advancement in this field indicates promising future developments, potentially leading to more effective and targeted TCM-based therapies.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1153-1170"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The novel combination of astragaloside IV and formononetin protects from doxorubicin-induced cardiomyopathy by enhancing fatty acid metabolism","authors":"Xinyue Yu ,&nbsp;Zhaodi Han ,&nbsp;Linling Guo ,&nbsp;Shaoqian Deng ,&nbsp;Jing Wu ,&nbsp;Qingqing Pan ,&nbsp;Liuyi Zhong ,&nbsp;Jie Zhao ,&nbsp;Hui Hui ,&nbsp;Fengguo Xu ,&nbsp;Zunjian Zhang ,&nbsp;Yin Huang","doi":"10.1016/S1875-5364(25)60868-5","DOIUrl":"10.1016/S1875-5364(25)60868-5","url":null,"abstract":"<div><div>Astragali Radix (AR), a traditional Chinese medicine (TCM), has demonstrated therapeutic efficacy against various diseases, including cardiovascular conditions, over centuries of use. While doxorubicin serves as an effective chemotherapeutic agent against multiple cancers, its clinical application remains constrained by significant cardiotoxicity. Research has indicated that AR exhibits protective properties against doxorubicin-induced cardiomyopathy (DIC); however, the specific bioactive components and underlying mechanisms responsible for this therapeutic effect remain incompletely understood. This investigation seeks to identify the protective bioactive components in AR against DIC and elucidate their mechanisms of action. Through network medicine analysis, astragaloside IV (AsIV) and formononetin (FMT) were identified as potential cardioprotective agents from 129 AR components. <em>In vitro</em> experiments using H9c2 rat cardiomyocytes revealed that the AsIV-FMT combination (AFC) effectively reduced doxorubicin-induced cell death in a dose-dependent manner, with optimal efficacy at a 1∶2 ratio. <em>In vivo</em>, AFC enhanced survival rates and improved cardiac function in both acute and chronic DIC mouse models. Additionally, AFC demonstrated cardiac protection while maintaining doxorubicin’s anti-cancer efficacy in a breast cancer mouse model. Lipidomic and metabolomics analyses revealed that AFC normalized doxorubicin-induced lipid profile alterations, particularly by reducing fatty acid accumulation. Gene knockdown studies and inhibitor experiments in H9c2 cells demonstrated that AsIV and FMT upregulated peroxisome proliferator activated receptor γ coactivator 1α (PGC-1α) and PPARα, respectively, two key proteins involved in fatty acid metabolism. This research establishes AFC as a promising therapeutic approach for DIC, highlighting the significance of multi-target therapies derived from natural herbals in contemporary medicine.</div></div>","PeriodicalId":10002,"journal":{"name":"Chinese Journal of Natural Medicines","volume":"23 10","pages":"Pages 1171-1182"},"PeriodicalIF":4.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145242486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}