Article(id=1320166350614549386, tenantId=1146029695717560320, journalId=1260987677001138203, issueId=1320166220377215955, articleNumber=null, orderNo=null, doi=10.13386/j.issn1002-0306.2025040227, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1744905600000, receivedDateStr=2025-04-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792681785490, onlineDateStr=2026-10-22, pubDate=1780243200000, pubDateStr=2026-06-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792681785490, onlineIssueDateStr=2026-10-22, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792681785490, creator=13701087609, updateTime=1792681785490, updator=13701087609, issue=Issue{id=1320166220377215955, tenantId=1146029695717560320, journalId=1260987677001138203, year='2026', volume='47', issue='11', pageStart='1', pageEnd='514', issueExtLink='null', onlineDate='null', pubDate='1780243200000', pubDateStr='2026-06-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792681754440, creator='13701087609', updateTime=1792681754440, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=88, endPage=99, ext={EN=ArticleExt(id=1320166352367768459, articleId=1320166350614549386, tenantId=1146029695717560320, journalId=1260987677001138203, language=EN, title=Hypolipidemic Effects of Medicinal and Edible Plant Extracts Based on Network Pharmacology and Molecular Docking, columnId=1261336277291548795, journalTitle=Science and Technology of Food Industry, columnName=Research and Investigation, runingTitle=null, highlight=null, articleAbstract=

To investigate the active components and hypolipidemic effects of medicinal and edible plants, this study evaluated eight species (foxtail millet, coix seed, tangerine peel, hawthorn, lotus leaf, mulberry leaf, cassia seed, and ginseng) through quantitative analysis of bioactive compounds, antioxidant capacity, and lipid metabolism-related functional indices, followed by cluster analysis and principal component analysis. Network pharmacology and molecular docking were further employed to identify potential hypolipidemic targets and pathways. Results demonstrated that lotus leaf exhibited the highest flavonoid (75.81±2.87 mg RE/g DW) and total phenolic content (38.63±0.88 mg GAE/g DW), while hawthorn showed the highest total sugar content (67.54±1.13 mg DE/g DW). Notably, hawthorn displayed potent inhibitory effects on pancreatic lipase (1.59±0.04 μg Orlistat/g DW), α-amylase (4.26±0.23 mg Acarbose/g DW), and α-glucosidase (87.46±0.97 μg Acarbose/g DW), along with superior sodium glycocholate binding capacity (59.24%) and cholesterol adsorption (9.57 mg/g). Network pharmacology revealed that hawthorn, lotus leaf, and coix seed primarily targeted lipid metabolism and atherosclerosis pathways, particularly through insulin resistance regulation. Molecular docking simulations revealed that key bioactive compounds (including stigmasterol, sitosterol, and rutin) exhibited strong binding affinities with core targets (INS, ALB, IL-6, etc.). These findings highlight hawthorn, lotus leaf, and coix seed as promising candidates for developing natural hypolipidemic functional foods, supported by multi-omics evidence.

, authors=Hui ZHANG1, Lingzhi ZHANG1, Xin ZHANG2, Yuanliang WANG1, Yu XIAO1, *, Wenping KONG3, *, authorsList=Hui ZHANG, Lingzhi ZHANG, Xin ZHANG, Yuanliang WANG, Yu XIAO, Wenping KONG, authorCompany=null, correspAuthors=Yu XIAO, Wenping KONG, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2026 Science and Technology of Food Industry. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320166357568705444, articleId=1320166350614549386, tenantId=1146029695717560320, journalId=1260987677001138203, language=CN, title=基于网络药理学与分子对接研究不同药食同源植物提取液的降脂作用, columnId=1261336277849391232, journalTitle=食品工业科技, columnName=研究与探讨, runingTitle=null, highlight=null, articleAbstract=

为研究不同药食同源植物活性成分含量及其降脂作用,该试验测定了八种不同药食同源植物(小米、薏仁、陈皮、山楂、荷叶、桑叶、决明子和人参)水提液的多个活性成分含量、抗氧化活性以及与脂代谢有关的功能指标,并对其进行聚类分析和主成分分析;进一步通过网络药理学和分子对接技术挖掘其多个降脂作用靶点及途径。结果表明,荷叶的黄酮、总酚含量最高,分别为(75.81±2.87)mg RE/g DW、(38.63±0.88)mg GAE/g DW;山楂的总糖含量最高,为(67.54±1.13)mg DE/g DW。此外,山楂对胰脂肪酶、α-淀粉酶、α-葡萄糖苷酶三种酶活表现出较强的抑制能力,分别为(1.59±0.04)μg Orlistat/g DW、(4.26±0.23)mg Acarbose/g DW、(87.46±0.97)μg Acarbose/g DW;同时对甘氨胆酸钠的结合能力和胆固醇吸附作用最好,分别为59.24%、9.57 mg/g。网络药理学分析揭示,山楂、荷叶和薏仁的潜在降脂靶点主要集中在脂质与动脉粥样硬化、胰岛素抵抗等途径。分子对接模拟结果显示,关键活性成分(如豆甾醇、谷甾醇和芸香苷)与核心靶点(INS、ALB、IL-6等)具有较高的结合亲和力。综上,山楂、荷叶和薏仁在降脂方面表现出良好的应用前景,为开发基于天然产物的降脂功能性食品提供了科学依据。

, authors=张惠1, 张灵芝1, 张鑫2, 王远亮1, 肖愈1, *, 孔文平3, *, authorsList=张惠, 张灵芝, 张鑫, 王远亮, 肖愈, 孔文平, authorCompany=null, correspAuthors=肖愈, 孔文平, authorNote=

张惠(2000−),女,硕士研究生,研究方向:药食同源,E-mail:

, correspAuthorsNote=
肖愈(1989−),男,博士,副教授,研究方向:食品微生物与发酵食品,天然产物生物转化与活性评价,E-mail:。
孔文平(1992−),男,博士,讲师,研究方向:益生菌与药食同源产品开发,天然产物生物合成与活性评价,E-mail:。
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Journal of Guizhou Medical University, 2025, 50(3): 346−360., articleTitle=null, refAbstract=null), Reference(id=1320166901158887547, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=42, rfOrder=67, authorNames=null, journalName=null, refType=null, unstructuredReference=SHAHZADI Z, YOUSAF Z, ANJUM I, et al. Network pharmacology and molecular docking: Combined computational approaches to explore the antihypertensive potential of Fabaceae species[J]. Bioresources and Bioprocessing, 2024, 11: 53., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320166883819635688, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, xref=1, ext=[AuthorCompanyExt(id=1320166883828024297, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166883819635688, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1College of Food Science and Technology, Hunan Agricultural University, Changsha 410128, China), AuthorCompanyExt(id=1320166883840607210, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166883819635688, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1湖南农业大学食品科学技术学院,湖南长沙 410128)]), AuthorCompany(id=1320166885497357291, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, xref=2, ext=[AuthorCompanyExt(id=1320166885509940204, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166885497357291, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2College of Food Science and Engineering, Ningbo University, Ningbo 315211, China), AuthorCompanyExt(id=1320166885526717421, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166885497357291, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2宁波大学食品科学与工程学院,浙江宁波 315211)]), AuthorCompany(id=1320166885618992110, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, xref=3, ext=[AuthorCompanyExt(id=1320166885631575023, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166885618992110, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3School of Nursing, Gannan Medical University, Ganzhou 341000, China), AuthorCompanyExt(id=1320166885648352240, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, companyId=1320166885618992110, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3赣南医科大学护理学院,江西赣州 341000)])], figs=[ArticleFig(id=1320166888240431128, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.1, caption=Contents of active ingredients in different water extracts, figureFileSmall=rAqXHF5Ed837fHkwwRCEew==, figureFileBig=NeZWpLD2Uj93Ufu2E6Vhsw==, tableContent=null), ArticleFig(id=1320166888294957081, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图1, caption=不同水提液活性成分含量

注:(a)总黄酮含量;(b)总酚含量;(c)总糖含量;不同小写字母表示组间差异显著(P<0.05),图2~图5同。

, figureFileSmall=rAqXHF5Ed837fHkwwRCEew==, figureFileBig=NeZWpLD2Uj93Ufu2E6Vhsw==, tableContent=null), ArticleFig(id=1320166889981067290, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.2, caption=Antioxidant capacity of different water extracts, figureFileSmall=TzwbhHQ7Sc2SaRNULNKQwA==, figureFileBig=5bKPlrdl8W29DNM10MbPNg==, tableContent=null), ArticleFig(id=1320166890153033755, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图2, caption=不同水提液的抗氧化能力

注:(a)ABTS+自由基清除能力;(b)DPPH自由基清除能力;(c)羟基自由基清除能力;(d)铁离子还原能力;(e)还原潜力。

, figureFileSmall=TzwbhHQ7Sc2SaRNULNKQwA==, figureFileBig=5bKPlrdl8W29DNM10MbPNg==, tableContent=null), ArticleFig(id=1320166890207559708, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.3, caption=Inhibition ability of different extracts on pancreatic lipase activity, figureFileSmall=Nhc4vootO6Bm6fB8zUykFA==, figureFileBig=re2z18vK467T3dbfVlwLlw==, tableContent=null), ArticleFig(id=1320166890274668574, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图3, caption=不同水提液对糖脂消化酶活性抑制效果

注:(a)胰脂肪酶活性抑制能力;(b)α-葡萄糖苷酶活性抑制能力;(c)α-淀粉酶活性抑制能力;ND:未检测到。

, figureFileSmall=Nhc4vootO6Bm6fB8zUykFA==, figureFileBig=re2z18vK467T3dbfVlwLlw==, tableContent=null), ArticleFig(id=1320166890333388831, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.4, caption=Inhibition ability of different water extracts on cholesterol esterase activity, figureFileSmall=g8sRkYZ46yQyiJNg+zjQbA==, figureFileBig=f9bHyYhUPD+2o8/ifbscow==, tableContent=null), ArticleFig(id=1320166890434052128, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图4, caption=不同水提液对胆固醇酯酶活性抑制能力, figureFileSmall=g8sRkYZ46yQyiJNg+zjQbA==, figureFileBig=f9bHyYhUPD+2o8/ifbscow==, tableContent=null), ArticleFig(id=1320166890522132513, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.5, caption=Cholesterol adsorption capacity of different water extracts, figureFileSmall=LQT/gP1YXpHbMgCf00HoqQ==, figureFileBig=eXKazwO9nkQZXf4EdqpXOA==, tableContent=null), ArticleFig(id=1320166890572464162, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图5, caption=不同水提取液对胆固醇吸附能力, figureFileSmall=LQT/gP1YXpHbMgCf00HoqQ==, figureFileBig=eXKazwO9nkQZXf4EdqpXOA==, tableContent=null), ArticleFig(id=1320166890647961635, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.6, caption=Principal component and load analysis diagram of different water extracts, figureFileSmall=ur8NDviy9wqsMqYx8VPdtQ==, figureFileBig=MPuQNDmxsQCPYB8B0JHp5w==, tableContent=null), ArticleFig(id=1320166890715070500, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图6, caption=不同水提取液主成分、载荷分析图

注:(a)主成分图;(b)载荷图,X:图中所有变量指标。

, figureFileSmall=ur8NDviy9wqsMqYx8VPdtQ==, figureFileBig=MPuQNDmxsQCPYB8B0JHp5w==, tableContent=null), ArticleFig(id=1320166890786373669, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.7, caption=Hierarchical cluster of different water extracts, figureFileSmall=WK4b65ml+3YZR3FSS3/SqQ==, figureFileBig=TBUCM5DAUWsYP+yXY4qsbQ==, tableContent=null), ArticleFig(id=1320166890949951526, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图7, caption=不同水提取液聚类分析, figureFileSmall=WK4b65ml+3YZR3FSS3/SqQ==, figureFileBig=TBUCM5DAUWsYP+yXY4qsbQ==, tableContent=null), ArticleFig(id=1320166891029643303, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.8, caption=Venn diagram of intersecting targets, figureFileSmall=9tXaHx+gG7OXxcO85qSPSA==, figureFileBig=5rKnH6TKPkK0hrTgUkabsQ==, tableContent=null), ArticleFig(id=1320166891088363560, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图8, caption=交集靶点韦恩图

注:绿色为药物靶点数,蓝色为疾病靶点数。

, figureFileSmall=9tXaHx+gG7OXxcO85qSPSA==, figureFileBig=5rKnH6TKPkK0hrTgUkabsQ==, tableContent=null), ArticleFig(id=1320166891159666729, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.9, caption=Drug component-disease-core target network, figureFileSmall=iHWkynHaY2aQXH3DzOr+0g==, figureFileBig=LjXmHSJThVWDFfuqA8aUOQ==, tableContent=null), ArticleFig(id=1320166891591680042, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图9, caption=药物成分-疾病-核心靶点图, figureFileSmall=iHWkynHaY2aQXH3DzOr+0g==, figureFileBig=LjXmHSJThVWDFfuqA8aUOQ==, tableContent=null), ArticleFig(id=1320166891788812331, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.10, caption=GO function and KEGG pathway enrichment results of potential lipid-lowering targets, figureFileSmall=YUBYUM+paN/QNxUy6aQyjg==, figureFileBig=YRi8brugL4iDX366TgGknQ==, tableContent=null), ArticleFig(id=1320166891860115500, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图10, caption=潜在降脂靶点GO功能、KEGG通路富集结果

注:(a)GO富集分析气泡图;(b)KEGG通路富集分析气泡图。

, figureFileSmall=YUBYUM+paN/QNxUy6aQyjg==, figureFileBig=YRi8brugL4iDX366TgGknQ==, tableContent=null), ArticleFig(id=1320166891948195885, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.11, caption=Compound-target-pathway network, figureFileSmall=X7mfm3idB/qDbWT/Pzdi2w==, figureFileBig=0lRNtHoulnktIbD8G6Qw6g==, tableContent=null), ArticleFig(id=1320166892023693358, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图11, caption=成分-靶点-通路图

注:HY(1~11):荷叶(槲皮素、异鼠李素、谷甾醇、山奈酚、乌药碱、O-去甲基荷叶碱、荷叶碱、白矢车菊苷元、莲碱、(+)-表儿茶素、儿茶素);SZ(1~9):山楂(α-香树脂醇、绿原酸、Chlorogenin、柠檬酸、表儿茶素、金丝桃苷、芦丁、熊果酸、牡荆素);YYR(1~9):薏仁(柠檬二烯醇、亚油酸乙酯、角鲨烯、甘油单油酸酯、谷甾醇、豆甾醇、Coixenolide、2-十八烯酸单甘油酯、CLR)。

, figureFileSmall=X7mfm3idB/qDbWT/Pzdi2w==, figureFileBig=0lRNtHoulnktIbD8G6Qw6g==, tableContent=null), ArticleFig(id=1320166892094996527, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Fig.12, caption=Visualization results of molecular docking, figureFileSmall=bsFH7ggyBQB7IY9XI+Wvsw==, figureFileBig=shaKJyzN5D/hcyYzoFyS+w==, tableContent=null), ArticleFig(id=1320166892187271216, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=图12, caption=分子对接可视化结果

注:(a):豆甾醇-ALB分子对接可视化图;(b):谷甾醇-TNF分子对接可视化图;(c):豆甾醇-TNF分子对接可视化图。

, figureFileSmall=bsFH7ggyBQB7IY9XI+Wvsw==, figureFileBig=shaKJyzN5D/hcyYzoFyS+w==, tableContent=null), ArticleFig(id=1320166892258574385, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Table 1, caption=

Cholate binding ability of different water extracts

, figureFileSmall=null, figureFileBig=null, tableContent=
胆酸盐胆酸盐相对结合量(μmol/10 mg)
小米薏仁陈皮山楂荷叶桑叶决明子人参
甘氨胆酸钠13.59±0.36f15.41±0.24e27.3±0.86c59.24±0.36a58.77±1.07a13.99±0.71ef42.44±0.85b18.9±0.6d
牛磺胆酸钠15.26±0.31g20.4±0.93f22.8±0.92e39.65±0.53b45.68±0.67a9.14±1.87h35.13±0.46c27.32±2.17d
), ArticleFig(id=1320166892342460466, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=表1, caption=

不同水提取液对胆酸盐结合能力

, figureFileSmall=null, figureFileBig=null, tableContent=
胆酸盐胆酸盐相对结合量(μmol/10 mg)
小米薏仁陈皮山楂荷叶桑叶决明子人参
甘氨胆酸钠13.59±0.36f15.41±0.24e27.3±0.86c59.24±0.36a58.77±1.07a13.99±0.71ef42.44±0.85b18.9±0.6d
牛磺胆酸钠15.26±0.31g20.4±0.93f22.8±0.92e39.65±0.53b45.68±0.67a9.14±1.87h35.13±0.46c27.32±2.17d
), ArticleFig(id=1320166892422152243, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Table 2, caption=

Node topology attributes in core component network analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
名称中介中心性接近中心性节点度
豆甾醇292.7980.00725.000
谷甾醇301.5660.00624.000
芸香苷255.3590.00621.000
), ArticleFig(id=1320166892510232628, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=表2, caption=

核心成分网络分析中节点拓扑属性

, figureFileSmall=null, figureFileBig=null, tableContent=
名称中介中心性接近中心性节点度
豆甾醇292.7980.00725.000
谷甾醇301.5660.00624.000
芸香苷255.3590.00621.000
), ArticleFig(id=1320166892594118709, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=EN, label=Table 3, caption=

Binding energies of key bioactive compounds with core targets

, figureFileSmall=null, figureFileBig=null, tableContent=
靶点成分结合能(kcal/mol)
INS谷甾醇Sitosterol−7.15
豆甾醇Stigmasterol−7.29
芸香苷Rutin−3.41
ALB豆甾醇Stigmasterol−11.07
谷甾醇Sitosterol−9.89
芸香苷Rutin−2.82
IL6豆甾醇Stigmasterol−7.74
谷甾醇Sitosterol−7.14
芸香苷Rutin−1.98
TNF豆甾醇Stigmasterol−10.61
谷甾醇Sitosterol−11.09
芸香苷Rutin−5.15
AKT1豆甾醇Stigmasterol−9.29
谷甾醇Sitosterol−9.13
芸香苷Rutin−4.61
), ArticleFig(id=1320166892669616182, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1320166350614549386, language=CN, label=表3, caption=

关键活性成分与核心靶点对接结合能

, figureFileSmall=null, figureFileBig=null, tableContent=
靶点成分结合能(kcal/mol)
INS谷甾醇Sitosterol−7.15
豆甾醇Stigmasterol−7.29
芸香苷Rutin−3.41
ALB豆甾醇Stigmasterol−11.07
谷甾醇Sitosterol−9.89
芸香苷Rutin−2.82
IL6豆甾醇Stigmasterol−7.74
谷甾醇Sitosterol−7.14
芸香苷Rutin−1.98
TNF豆甾醇Stigmasterol−10.61
谷甾醇Sitosterol−11.09
芸香苷Rutin−5.15
AKT1豆甾醇Stigmasterol−9.29
谷甾醇Sitosterol−9.13
芸香苷Rutin−4.61
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基于网络药理学与分子对接研究不同药食同源植物提取液的降脂作用
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张惠 1 , 张灵芝 1 , 张鑫 2 , 王远亮 1 , 肖愈 1, * , 孔文平 3, *
食品工业科技 | 研究与探讨 2026,47(11): 88-99
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食品工业科技 |研究与探讨 2026 , 47 (11) : 88 -99
基于网络药理学与分子对接研究不同药食同源植物提取液的降脂作用
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张惠1 , 张灵芝1, 张鑫2, 王远亮1, 肖愈1, * , 孔文平3, *
作者信息
  • 1湖南农业大学食品科学技术学院,湖南长沙 410128
  • 2宁波大学食品科学与工程学院,浙江宁波 315211
  • 3赣南医科大学护理学院,江西赣州 341000
通讯作者:
肖愈(1989−),男,博士,副教授,研究方向:食品微生物与发酵食品,天然产物生物转化与活性评价,E-mail:。
孔文平(1992−),男,博士,讲师,研究方向:益生菌与药食同源产品开发,天然产物生物合成与活性评价,E-mail:。
作者简介:

张惠(2000−),女,硕士研究生,研究方向:药食同源,E-mail:

Hypolipidemic Effects of Medicinal and Edible Plant Extracts Based on Network Pharmacology and Molecular Docking
Hui ZHANG1 , Lingzhi ZHANG1, Xin ZHANG2, Yuanliang WANG1, Yu XIAO1, * , Wenping KONG3, *
Affiliations
  • 1College of Food Science and Technology, Hunan Agricultural University, Changsha 410128, China
  • 2College of Food Science and Engineering, Ningbo University, Ningbo 315211, China
  • 3School of Nursing, Gannan Medical University, Ganzhou 341000, China
出版时间: 2026-06-01 doi: 10.13386/j.issn1002-0306.2025040227
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为研究不同药食同源植物活性成分含量及其降脂作用,该试验测定了八种不同药食同源植物(小米、薏仁、陈皮、山楂、荷叶、桑叶、决明子和人参)水提液的多个活性成分含量、抗氧化活性以及与脂代谢有关的功能指标,并对其进行聚类分析和主成分分析;进一步通过网络药理学和分子对接技术挖掘其多个降脂作用靶点及途径。结果表明,荷叶的黄酮、总酚含量最高,分别为(75.81±2.87)mg RE/g DW、(38.63±0.88)mg GAE/g DW;山楂的总糖含量最高,为(67.54±1.13)mg DE/g DW。此外,山楂对胰脂肪酶、α-淀粉酶、α-葡萄糖苷酶三种酶活表现出较强的抑制能力,分别为(1.59±0.04)μg Orlistat/g DW、(4.26±0.23)mg Acarbose/g DW、(87.46±0.97)μg Acarbose/g DW;同时对甘氨胆酸钠的结合能力和胆固醇吸附作用最好,分别为59.24%、9.57 mg/g。网络药理学分析揭示,山楂、荷叶和薏仁的潜在降脂靶点主要集中在脂质与动脉粥样硬化、胰岛素抵抗等途径。分子对接模拟结果显示,关键活性成分(如豆甾醇、谷甾醇和芸香苷)与核心靶点(INS、ALB、IL-6等)具有较高的结合亲和力。综上,山楂、荷叶和薏仁在降脂方面表现出良好的应用前景,为开发基于天然产物的降脂功能性食品提供了科学依据。

药食同源  /  活性成分  /  降脂  /  分子对接  /  网络药理学分析

To investigate the active components and hypolipidemic effects of medicinal and edible plants, this study evaluated eight species (foxtail millet, coix seed, tangerine peel, hawthorn, lotus leaf, mulberry leaf, cassia seed, and ginseng) through quantitative analysis of bioactive compounds, antioxidant capacity, and lipid metabolism-related functional indices, followed by cluster analysis and principal component analysis. Network pharmacology and molecular docking were further employed to identify potential hypolipidemic targets and pathways. Results demonstrated that lotus leaf exhibited the highest flavonoid (75.81±2.87 mg RE/g DW) and total phenolic content (38.63±0.88 mg GAE/g DW), while hawthorn showed the highest total sugar content (67.54±1.13 mg DE/g DW). Notably, hawthorn displayed potent inhibitory effects on pancreatic lipase (1.59±0.04 μg Orlistat/g DW), α-amylase (4.26±0.23 mg Acarbose/g DW), and α-glucosidase (87.46±0.97 μg Acarbose/g DW), along with superior sodium glycocholate binding capacity (59.24%) and cholesterol adsorption (9.57 mg/g). Network pharmacology revealed that hawthorn, lotus leaf, and coix seed primarily targeted lipid metabolism and atherosclerosis pathways, particularly through insulin resistance regulation. Molecular docking simulations revealed that key bioactive compounds (including stigmasterol, sitosterol, and rutin) exhibited strong binding affinities with core targets (INS, ALB, IL-6, etc.). These findings highlight hawthorn, lotus leaf, and coix seed as promising candidates for developing natural hypolipidemic functional foods, supported by multi-omics evidence.

medicine food homology  /  active ingredient  /  lipid-lowering  /  molecular docking  /  network pharmacology analysis
张惠, 张灵芝, 张鑫, 王远亮, 肖愈, 孔文平. 基于网络药理学与分子对接研究不同药食同源植物提取液的降脂作用. 食品工业科技, 2026 , 47 (11) : 88 -99 . DOI: 10.13386/j.issn1002-0306.2025040227
Hui ZHANG, Lingzhi ZHANG, Xin ZHANG, Yuanliang WANG, Yu XIAO, Wenping KONG. Hypolipidemic Effects of Medicinal and Edible Plant Extracts Based on Network Pharmacology and Molecular Docking[J]. Science and Technology of Food Industry, 2026 , 47 (11) : 88 -99 . DOI: 10.13386/j.issn1002-0306.2025040227
高脂血症(hyperlipidemia)是一种以血液脂蛋白代谢异常为主要特征的慢性代谢性疾病,临床上也称为血脂异常[1]。该疾病的典型生化特征表现为甘油三酯(TG)、总胆固醇(TC)和低密度脂蛋白胆固醇(LDL-C)水平升高,同时伴有高密度脂蛋白胆固醇(HDL-C)水平下降,这种改变显著增加心血管疾病、肥胖等代谢性共病的发生风险,因此高脂血症在临床上常表现出多病并发的特点[2]。然而,目前临床上用于治疗高脂血症的药物大部分为化学合成药物,长期使用存在明显的局限性,不仅容易产生一定的依赖性,难以有效控制高血脂引发的并发症,还可能导致严重的副作用[3],如引发肝功能损伤、肌肉毒性等不良反应[4],部分患者甚至出现血糖代谢异常等新的代谢紊乱。鉴于现有疗法的上述缺陷,促使研究者将目光转向“药性平和、毒副作用小”的药食同源植物。现代药理研究证实,多种药食同源植物(如山楂Crataegus pinnatifida、荷叶Nelumbo nucifera、桑叶Morus alba等)富含黄酮类、多糖类及多酚类活性成分,这些成分可通过多靶点、多途径发挥降脂作用,具有一定的研究意义[5−7]。
近年来,关于高脂血症的天然药物研究取得显著进展。研究表明,天然药食同源植物可通过多靶点、多通路发挥降脂作用,具体机制包括抑制外源性糖脂吸收、促进脂质代谢、改善胰岛素抵抗以及抗氧化等[8]。其中含有的多种活性成分具有抗氧化、调节血脂的功能,如黄酮类有效成分可能通过调节肠道微生物、改善肝功能,调控JAK2/STAT3等信号通路及PPAR-α等关键因子表达,减少脂肪合成[9];多糖类成分可调控脂质的合成分解、抑制脂质的易位堆积、减少氧化应激和炎症损伤等方面[10];多酚类活性成分则可以通过干预脂肪代谢和脂肪细胞分化等多途径减少脂肪沉积。周其其等[11]研究山楂叶中的黄酮物质对高脂血症肾损伤大鼠的保护作用,证明了山楂中的黄酮类化合物(如金丝桃苷、槲皮素等)能显著抑制磷酸化ACC的表达以提高脂肪酸的氧化。王韬等[12]通过研究薏苡仁油对小鼠肠道菌群及炎症因子的影响,证明了薏仁中的多糖成分则可以通过调节肠道菌群组成而影响胆汁酸代谢。Kim等[13]证明了荷叶水提物能通过促进甘油三酯分解为游离脂肪酸和甘油来抑制高脂饮食小鼠的脂肪蓄积,同时促进脂肪分解以降低脂肪合成。尽管上述研究揭示了单一成分的作用机制,但不同药食同源植物的系统性降脂效能比较及其作用机制研究仍显不足。
因此,本研究选取八种不同药食同源植物(山楂、陈皮、荷叶、决明子、薏仁、小米、桑叶和人参),通过测定其水提液中活性成分(黄酮、总酚、总糖)含量,体外抗氧化能力以及体外降脂能力,系统比较八种水提液的体外降脂作用。进一步结合网络药理学分析,基于筛选出的降脂活性显著的山楂、荷叶和薏仁水提液,通过多数据库挖掘其活性成分及作用靶点,构建PPI互作网络并进行GO功能与KEGG通路富集分析,系统预测其主要降脂作用机制。此外,采用分子对接技术模拟核心活性成分与关键靶点的结合模式,评估其相互作用潜力。本研究为开发具有降脂功效的功能性食品提供一定的理论依据与试验基础,同时为传统药食同源植物的现代化开发利用提供科学参考。
八种药食同源材料(薏仁、小米、陈皮、山楂、荷叶、桑叶、决明子、人参) 均来自于湖南润天药业股份有限公司;α-淀粉酶(3700 U·g−1) 索莱宝科技有限公司;4-硝基苯基 α-D-吡喃葡萄糖苷(PNPG)、胰脂肪酶(30000 U·g−1)、奥利司他(Orlistat)、人工肠液、人工胃液 上海源叶生物科技有限公司;α-葡萄糖苷酶(≥10 U/mg)、胆固醇酯酶(67.9 U·mg−1)、棕榈酸对硝基苯酯(PNPP)、阿卡波糖水合物、4-硝基苯基丁酸酯 上海麦克林生化科技有限公司;新鲜鸡蛋 联华超市;其余所用试剂 均来自国药集团化学试剂有限公司。
ABP00251全波长酶标仪 上海旦鼎国际贸易有限公司、XMTD-7000电热恒温水浴锅 天津市泰斯特仪器有限公司、3-18R高速冷冻离心机 美国贝克曼公司;RS-FS1406磨粉机 荣事达有限公司。
将八种药食同源材料用磨粉机粉碎,装入自封袋中。分别称取1 g粉末,添加超纯水(水:样品=40:1,v/w)于95 ℃水浴锅中热提取30 min,其中每隔5 min振荡一次。冷却后10000 r/min离心15 min,取上清液,定容到50 mL,避光保藏放在4 ℃冰箱中。
参照文献方法[14]并加以改进,精密吸取不同样品的水提液,采用亚硝酸钠-硝酸铝比色法测定样品中总黄酮含量,于相同条件下测定不同浓度(0、0.1、0.2、0.3、0.4、0.5 mg/mL)的芦丁标准溶液的吸光度,制作标准曲线,其方程为y=0.9207x+0.0002(R2=0.9995)。样品吸光度值代入标准曲线计算,最终结果以每克样品中含有的芦丁当量表示。
基于文献方法[15]进行改进,精密吸取不同样品的水提液,采用福林酚比色法测定样品总酚含量,于相同条件下测定不同浓度(0、10、50、80、100、120、150 μg/mL)的没食子酸标准溶液的吸光度,制作标准曲线,其方程为y=0.003x−0.0012(R2=0.9941)。样品吸光度值代入标准曲线计算,最终结果以每克样品中含有的没食子酸当量表示。
参照文献方法[16]并加以改进,同时精密吸取不同浓度(0、5、10、20、30、40、50 μg/mL)葡萄糖标准溶液,按照苯酚-硫酸法反应条件于490 nm处测定吸光度,并制作标准曲线,其方程为y=0.0092x+0.0003(R2=0.9988)。于相同条件下测定不同样品吸光度,样品吸光度值代入标准曲线计算,最终结果以每克样品中含有的葡萄糖当量表示。
根据文献方法[17]修改并测定,吸取0.2 mL样品溶液和浓度为0.4 mmol/L的DPPH甲醇溶液各0.5 mL,旋涡振荡混匀;避光反应30 min后于517 nm处测定吸光度值。绘制维生素C(0、2.5、10、12、18、25 μg/mL)标准曲线,其方程为y=0.0151x−0.0156(R2=0.9936),结果以每克样品中含有的维生素C当量表示。
根据文献方法[17]修改并测定,分别取0.2 mL样品溶液加入2 mL离心管;然后取0.8 mL ABTS工作液加入2 mL离心管中,混匀于室温下反应6 min;于734 nm处测定吸光度值。使用不同浓度的维生素C标准溶液(0、2.5、5、10、12、15、25、30 μg/mL)绘制标准曲线,其方程为y=0.0165x+0.0049(R2=0.9973),结果以每克样品中含有的维生素C当量表示。
根据文献方法[17]修改并测定,分别取1 mL试样溶液与1 mL浓度为9 mmol/L的硫酸亚铁溶液混合后,加入1 mL 8.8 mmol/L的H2O2溶液和1 mL 9 mmol/L的水杨酸-乙醇混合液并充分混匀。将反应体系置于37 ℃恒温水浴中反应60 min后,使用分光光度计在510 nm波长处测定吸光度值。使用不同浓度的维生素C标准溶液(0、0.5、2、2.5、3、3.5、4 mg/mL)绘制标准曲线,其方程为y=0.3335x−0.0409(R2=0.9933),结果以每克样品中含有的维生素C当量表示。
根据文献方法[17]修改并测定,分别取样品溶液0.2 mL,加入1 mL的FRAP溶液,在37 ℃下放置20 min,于593 nm处测定吸光度值。使用不同浓度FeSO4标准溶液(0、50、100、200、400、500、600、800、1000 μmol/L)绘制标准曲线,其方程为y=0.0023x+0.0087(R2=0.9982),结果以每克样品中含有的Fe(Ⅱ)当量表示。
根据文献方法[18]修改并测定,取0.5 mL待测样品,依次加入2.5 mL pH6.6的0.2 mol/L磷酸盐缓冲液和10 mg/mL K3[Fe(CN)6]溶液,混匀后于50 ℃水浴反应20 min。随后加入2.5 mL的100 mg/mL三氯乙酸溶液,充分振荡混匀后以2000 r/min离心10 min。吸取2.5 mL离心上清液,加入0.5 mL 1 mg/mL FeCl3溶液,静置反应10 min后在700 nm波长处测定吸光值。使用不同浓度的维生素C标准溶液(0、2.5、5、10、20、25、80、100 μg/mL)绘制标准曲线,其方程为y=0.0061x+0.0083(R2=0.9992),结果以每克样品中含有的维生素C当量表示。
根据文献方法[19]修改并测定,按以下反应体系在96 孔板中操作。首先取30 μL Tris-HCl缓冲液(50 mmol/L,pH8.0),加入50 μL胰脂肪酶溶液(1 mg/mL)和20 μL待测样品溶液,充分混匀后于37 ℃恒温孵育10 min。随后依次加入100 μL PNPP底物溶液(1 mmol/L)继续37 ℃反应15 min,然后测定各孔在405 nm波长下的吸光度。以奥利司他为阳性对照(0、0.000125、0.0025、0.005、0.02、0.04、0.06、0.08 μg/mL),并绘制奥利司他标准曲线,其方程为y=8.6995x+0.1801(R2=0.9912),最终结果以每克样品中含有的奥利司他当量表示。根据式(1)计算胰脂肪酶抑制率:
$\rm X({\text{%}})=\left(1-\frac{B-B_0}{A-A_0}\right)\times 100 $
式中:X:胰脂肪酶抑制率%;B:样品组的吸光度;B0:阴性对照组的吸光度(不加酶);A:未添加待测样品组的吸光度;A0:为A的空白对照组(不加酶)的吸光度。
根据文献方法[19]修改并测定,按以下反应体系进行,依次加入PBS(20 mmol/L pH6.9)、α-葡萄糖苷酶溶液(1 U/mL)和待测样品,混匀,37 ℃恒温10 min;加入对硝基苯基-α-D-吡喃葡萄糖苷溶液(2.5 mmol/L)并混匀,37 ℃恒温反应15 min;加入Na2CO3(0.2 mol/L)溶液后混匀,在405 nm波长下测定各孔吸光度。以阿卡波糖作阳性对照(0、0.005、0.01、0.02、0.04、0.06、0.08、0.1 μg/mL)并绘制阿卡波糖标准曲线,其方程为y=7.2341x+0.1602(R2=0.9924),最终结果以每克样品中含有的阿卡波糖当量表示。计算公式见式(2):
$ \rm Y({\text{%}})=\left(1-\frac{A_1-A_0}{A}\right)\times 100 $
式中:Y:α-葡萄糖苷酶抑制率%;A1:样品组的吸光度;A0:阴性对照组的吸光度(不加酶);A:未添加待测样品组的吸光度。
根据文献方法[20]修改并测定,按以下反应体系进行,在1.5 mL 离心管中依次加入PBS(20 mmol/L pH6.9)、α-淀粉酶溶液(0.2 U/mL)和样品溶液,混匀,37 ℃反应 5 min;加入淀粉溶液(质量分数为1%)混匀,37 ℃恒温反应10 min;再加入DNS溶液后混匀,在37 ℃恒温反应5 min后,立即沸水浴5 min,然后迅速冰水浴迅速冷却。最后加入400 μL蒸馏水稀释后,在540 nm波长下测定各孔吸光度。以阿卡波糖作阳性对照(0、0.01、0.02、0.06、0.08、0.1、0.14 mg/mL)并绘制阿卡波糖标准曲线,其方程为y=0.0041x+0.1021(R2=0.9913),最终结果以每克样品中含有的阿卡波糖当量表示。计算公式同式(2)。
根据文献方法[15]修改并测定,按以下反应体系进行,取1 mL(0.1 mol/L,pH7.0)缓冲液,80 μL酶液(100 U、7.2 U/mL),200 μL样品溶液和20 μL 4 mmol/L底物4-硝基苯基丁酸酯于离心管中,混匀,25 ℃反应0.5 h,于波长405 nm处测吸光度,以奥利司他作阳性对照(0、0.08、0.32、0.48、0.64、0.8 μg/mL),测定各孔在405 nm波长下的吸光度,并绘制奥利司他标准曲线,其方程为y=1.1196x−0.0335(R2=0.9903),最终结果以每克样品中含有的奥利司他当量表示。计算公式同式(1)。
根据文献方法[21]修改并测定,准确量取1 mL待测样品(10 mg/mL)置于10 mL离心管中,加入1 mL模拟胃液,37 ℃恒温振荡消化1 h;用0.1 mol/L氢氧化钠溶液调pH至6.3后,加入4 mL模拟肠液,37 ℃恒温振荡反应1 h;随后分别加入4 mL甘氨胆酸盐与牛磺胆酸盐溶液(0.5 mmol/L),37 ℃恒温振荡反应1 h;以4000 r/min的转速离心20 min后,准确移取2 mL上清液备用;加入6 mL 60%浓硫酸溶液,70 ℃水浴加热20 min,冷却至室温;于387 nm处测定吸光度值。并绘制标准曲线(0、0.1、0.2、0.3、0.4、0.5 mmol/L),甘氨胆酸盐标准曲线方程为y=0.4206x+0.0235(R2=0.9902)、牛磺胆酸盐标准曲线方程为y=0.3758x+0.021(R2=0.9905)。按公式(3)计算实际胆酸盐结合能力。
$\rm A={A}_{0}-\left({A}_{2}-{A}_{1}\right) $
式中:A0:以 PBS 代替样品的吸光度值;A1:以PBS代替胆酸盐溶液的吸光度值;A2:样品管的吸光度值。
根据文献方法[22]修改并测定,将新鲜蛋黄与9倍体积蒸馏水混合均匀后,准确称取25 g稀释蛋黄液置于100 mL锥形瓶,加入1 g待测样品溶液,调节pH至7.0后置于37 ℃恒温振荡器中以120 r/min振荡反应2 h。反应结束后吸取0.4 mL上清液,采用邻苯二甲醛法,于550 nm波长下测定吸光度,并绘制标准曲线(0、0.1、0.4、0.5、0.6、0.7、0.8 mg/mL),标准曲线方程为y=2.7311x+0.0209(R2=0.9954),代入公式(4)计算。
$ \rm B=\frac{m_1-m_2}{M} $
式中:m1:吸附前胆固醇含量(mg),m2:吸附后胆固醇含量(mg),M:样品质量(g)。
通过ETCM(http://www.tcmip.cn/)、TCMSP(http://lsp.Nwu.Edu.cn/tcmsp.php)、SwissTargetPrediction (http://www.swisstargetprediction.ch/)数据库搜索主要活性成分及其对应靶点,舍弃重复项,筛选后得到关键靶点,通过UniProt等数据库转换,即得其对应靶点基因名称[23]。
疾病靶点基因的筛选基于GeneCards(https://www.genecards.org/)、DISGENET(https://disgenet.com/)和OMIM数据库(https://www.omim.org/),输入关键词,检索并搜集有关靶点,对结果汇总后删除重复基因,即得有关基因。
将数据导入STRING(https://stringdb-orgs.libproxy.xmu.edu.cn:443)分析后得到交集靶点,利用Cytoscape3.9.1构建山楂、薏苡仁、荷叶与疾病的共同靶蛋白的蛋白质相互作用(PPI)网络,并进行分析。
运用DAVID在线分析平台(https://david.ncifcrf.gov/)对关键作用靶点开展KEGG通路富集研究和GO功能分析,从分子通路和生物学功能两个层面阐释其可能的降血糖调血脂作用机理。采用KEGG通路散点图和GO富集散点图对分析数据进行可视化展示。
基于PPI网络中MCC算法的拓扑分析结果,选取网络中心度排名前五的核心靶点及与节点度最高的三种活性化合物开展分子对接研究。从PubChem(https://pubchem.ncbi.nlm.nih.gov/)化学数据库中下载所筛选化合物的三维结构信息:豆甾醇(Stigmasterol,PubChem ID:5280794)、谷甾醇(Sitosterol,PubChem ID:222284)和芸香苷(Rutin,PubChem ID:5280805),关键靶点蛋白分别为胰岛素(INS,PDB ID:1mso)、白蛋白(ALB,PDB ID:1n5u)、白细胞介素-6(IL6,PDB ID:5gw9)、肿瘤坏死因子(TNF,PDB ID:6q00)和蛋白激酶B1(AKT1,PDB ID:7myx),其晶体结构从RCSB PDB数据库(https://www.rcsb.org/)获取。并通过PDB蛋白质数据库下载关键靶点蛋白的晶体结构文件,然后经过Pymol 4.60对蛋白结构进行去除水分子、提取配体处理后,采用AutoDock1.5.6软件加氢处理并对配体与受体进行分子对接模拟,以结合自由能为评价指标,分析其相互作用能[24]。
所有试验均进行3次独立重复测定,数据以均值±标准差(mean±SD)表示。采用SPSS 20.0软件对数据进行统计分析,组间比较采用单因素方差分析(ANOVA)及LSD事后检验。显著性水平设为P<0.05。数据可视化用Origin 2021与SPSS 20.0完成。
图1为不同植物水提液的活性成分含量,如图1a~图1c所示,不同样品间的三种活性成分含量均存在显著差异(P<0.05)。其中,荷叶提取物含有最高的总黄酮(75.81±2.87 mg RE/g DW)和总酚含量(38.63±0.88 mg GAE/g DW)。已有研究表明,荷叶富含黄酮类物质(如槲皮素、芦丁等),而槲皮素类黄酮化合物具有改善高脂饮食诱导的肥胖、减少脂质沉积的作用[25]。山楂中的总黄酮、总酚含量次之,分别为(44.31±3.2)mg RE/g DW、(25.08±1.07)mg GAE/g DW。山楂中的黄酮类活性成分主要来源于金丝桃苷、原花青素等物质,李贵海等[26]研究表明,金丝桃苷组分一定调节血脂和胆固醇代谢的功效,这为山楂的降脂功效提供了理论依据。相比之下,小米、薏仁和人参样品中的总黄酮和总酚含量显著低于荷叶(P<0.05)。其中人参中总黄酮为(0.93±0.03)mg RE/g DW,小米总酚为(0.58±0.09)mg GAE/g DW。由图1c则可知,山楂的总糖含量最高,为(67.54±1.13)mg DE/g DW,而人参的总糖含量最低,为(15.15±0.38)mg DE/g DW。
不同提取液的体外抗氧化能力如图2所示,由图可知,8种不同水提取液在5种抗氧化能力测定结果中均表现出显著性差异(P<0.05)。其中,荷叶和山楂水提液的综合抗氧化能力最强。荷叶水提液对ABTS+和羟基自由基的清除能力最高,分别为(29.30±0.37)mg VCE/g DW和(78.70±2.25)mg VCE/g DW。山楂水提液的DPPH自由基清除能力(53.55±0.11)mg VCE/g DW、铁离子还原能力(68.73±0.96)mg FeSO4/g DW及还原潜力(42.08±0.71)mg VCE/g DW最强。有研究表明,植物中的多酚和黄酮含量与其抗氧化活性呈正相关[8],因此黄酮和总酚含量较高的荷叶与山楂水提液表现出更强的抗氧化能力。
图3为不同水提取液对不同糖脂代谢酶酶活抑制能力结果,由图可知,8种不同水提液对三种糖脂代谢酶酶活抑制能力存在显著性差异(P<0.05)。其中,胰脂肪酶作为脂肪分解的关键酶,其主要功能体现在促进甘油三酯分解为甘油和游离脂肪酸[27];在糖代谢方面,α-葡萄糖苷酶直接影响肠道葡萄糖吸收效率[28],而α-淀粉酶则是淀粉转化为葡萄糖过程中的限速酶。这三种酶的活性抑制程度与糖脂代谢调控密切相关,特别是胰脂肪酶活性的抑制对于高脂血症等代谢性疾病的防治具有重要价值。由图3可知,山楂水提液表现出最强的胰脂肪酶酶活抑制能力(1.59±0.04 μg Orlistat/g DW),荷叶提取液次之(1.45±0.12 μg Orlistat/g DW),这可能归因于两者富含的黄酮及多酚类活性成分[29]。在α-葡萄糖苷酶活性抑制方面,山楂(87.46±0.97 μg Acarbose/g DW)和荷叶(41.18±1.38 μg Acarbose/g DW)水提液抑制能力与其余6组相比同样显著(P<0.05)。文献指出,山楂中的槲皮素、熊果酸等黄酮成分通过非竞争性抑制机制作用于α-葡萄糖苷酶,而荷叶中的生物碱类物质也显示出显著的酶抑制活性[30−31]。此外,在α-淀粉酶抑制试验中,山楂水提液相较于其余7组也表现出显著抑制活性(4.26±0.23 mg Acarbose/g DW),这一结果与陶益等[32]报道的山楂黄酮类物质对α-淀粉酶的抑制作用相吻合。荷叶水提液同样显示出明显的抑制效果(2.28±0.07 mg Acarbose/g DW)。
如图4所示,八种水提液对胆固醇酯酶活性均表现出不同程度的抑制作用(P<0.05)。作为脂质代谢的关键酶,胆固醇酯酶参与胆固醇酯和甘油三酯的水解过程[33]。因此说明,水提取液可以通过抑制该酶活性,减少肠道对膳食胆固醇的吸收,从而发挥调节血脂的潜在功效。结果显示,薏仁水提液对胆固醇酯酶的抑制能力最强,为(26.72±0.82)μg Orlistat/g DW。研究表明,薏苡仁奶可以降低小鼠体内低密度脂蛋白胆固醇的水平[34],结合此试验结果,推测薏仁降低胆固醇的作用途径可能与抑制胆固醇酯酶活性有关。相比之下,桑叶提取液对胆固醇酯酶的抑制活性最低,为(4.99±0.27)μg Orlistat/g DW,薏仁抑制效果约为其5.4倍。因此,可以考虑利用薏仁对胆固醇酯酶活性的抑制作用来降血脂。
表1为不同水提取液对胆酸盐结合能力结果。人体中肝脏胆汁酸常以钠盐或钾盐的形式存在,并与甘氨酸或牛磺酸结合,形成甘氨胆酸钠和牛磺胆酸钠两种结合型胆酸盐[35]。这些胆酸盐有助于小肠对脂肪的吸收和胆固醇的降解,因此胆酸盐结合能力可作为评价降血脂功效的重要指标。由表1可知,这八种水提取液对两种胆酸盐均有一定的结合能力,表明它们均可促使胆酸盐排出体外从而加速胆固醇的排泄代谢,发挥降脂作用。山楂、荷叶水提液分别对甘氨胆酸钠和牛磺胆酸钠的结合能力最强。有研究表明,荷叶中黄酮类成分可通过增强胆酸盐结合能力发挥降脂作用[36]。本研究结果进一步验证了这一结论,并为山楂和荷叶的降脂功效提供了新的试验证据。
图5为不同水提取液的胆固醇吸附能力结果。机体内胆固醇含量过高,会增加高血脂、心血管等疾病的风险[37],因此有效降低胆固醇含量,可以减少人体患病的风险。由图5可知,八种不同样品均对胆固醇有不同程度的吸附能力。其中,山楂对胆固醇吸附能力最高,为9.57 mg/g,其次为荷叶,为9.21 mg/g,吸附能力最小的为陈皮,为2.84 mg/g,并且山楂的吸附能力为陈皮的3.37倍,样品间表现出显著差异(P<0.05)。进一步结合胆固醇酯酶活性抑制能力、胆酸盐结合能力两个指标可知,山楂、荷叶水提取液在这三个评价指标中均表现出优异的降胆固醇效果。其作用机制可能包括:直接吸附消化道中的胆固醇;抑制胆固醇酯酶的活性;促进胆酸盐的排泄[38]。这种多靶点的协同作用使得山楂和荷叶在调节胆固醇代谢方面表现出显著优势。
基于以上试验结果构建PCA图进行数据可视化。如图6a所示,PCA分析有效区分了八种植物提取液样品,两个主成分累计贡献率达83.6%,充分反映了样本间的主要差异。空间分布显示,荷叶、山楂位于评分图右侧区域,桑叶位于中间区域,其余样品(小米、陈皮、薏仁、决明子、人参)集中分布于左侧象限。载荷分析(图6b)进一步揭示了影响样本分异的关键变量,反映了影响不同样品的活性成分含量和各种功能指标间的分布情况。由图可知,除胆固醇酯酶活性抑制能力和总糖活性成分含量外,绝大多数活性成分(总黄酮、总酚)和功能指标(胰脂肪酶抑制、α-葡萄糖苷酶抑制等)的载荷向量均与山楂、荷叶的投影位置紧密关联。这一发现从统计学角度解释了二者降脂作用相似性的基础。
对这八种样品进行聚类分析,如图7所示,当类间距离为3时,可以将八种样品分为三类,一类为山楂、荷叶;一类为桑叶,另一类为小米、陈皮、薏仁、决明子和人参,这与主成分分析结果相符合。综上,山楂和荷叶在活性成分含量与功能特性上呈现明显的聚类特征,表明二者在调节脂代谢能力方面可能具有相似性,桑叶和薏仁呈现出较独特的活性特征;而其他四种样品在活性成分和功能上具有较高相似性。以上分析为后续功能产品开发的原料筛选或者复配提供了一定科学依据,特别是验证了山楂和荷叶作为核心原料的优越性。
基于上述试验结果,综合各项功能指标表明山楂、荷叶在降脂方面具有显著潜力,薏仁在抑制胆固醇酯酶方面表现出较好的降胆固醇作用。因此,选择山楂、荷叶和薏仁三种物质,利用网络药理学分析继续进一步分析其降脂机制。首先通过GeneCards、OMIM数据库,以高血脂为关键词进行搜索,整理后共得到2106个疾病靶点。然后通过TCMSP和SwissTargetPrediction数据库搜索山楂、薏仁、荷叶的靶点,整理后得到1304个药物靶点。将以上药物靶点和疾病靶点求交集得到交集靶点218个(图8)。
通过STRING数据库构建218个降脂潜在靶点的PPI网络,并利用MCC算法筛选出核心靶点INS(胰岛素)、ALB(白蛋白)和IL-6(白细胞介素-6)(图9)。这些靶点在度值、介数、接近中心性等拓扑参数中显著突出,表明其在网络中的核心地位。INS通过调控脂质合成与能量代谢参与降脂作用;ALB作为脂质运输的关键载体;IL-6则介导炎症反应与代谢紊乱[39−41]。三者与其他靶点广泛互作,形成覆盖脂代谢、炎症及胰岛素信号通路的协同网络,提示山楂、薏仁、荷叶可能通过多靶点调控机制,如改善脂代谢紊乱、抑制炎症等协同发挥降脂效应。为阐释山楂、薏苡仁、荷叶逆转高血脂症的分子机制提供了重要的理论依据,并为后续深入研究和临床应用奠定了基础。
经GO富集分析共获得806条GO富集分析条目,其中包含572个生物过程(BP)、78个细胞组分(CC)和156个分子功能(MF)。选取各富集过程的前10个条目进行可视化分析(图10a)。BP富集分析结果显示,主要条目涉及对异生物质刺激的反应(response to xenobiotic stimulus)、基因表达的正负调控(positive/negative regulation of gene expression)等;CC富集分析结果主要涉及细胞外空间(extracellular space)、细胞外分泌体(extracellular exosome)等;MF富集分析结果主要涉及酶结合(enzyme binding)、氧化还原酶活性(oxidoreductase activity)、蛋白质同源二聚化活性(protein homodimerization activity)、相同蛋白质结合(identical protein binding)、染色质结合(chromatin binding)以及ATP结合(ATP binding)等过程。
KEGG富集分析共鉴定出150条相关信号通路,通过对排名前20的通路进行聚类分析并绘制气泡图(图10b)。结果表明,山楂、薏仁和荷叶的作用靶点显著富集于胰岛素抵抗(Insulin resistance)、HIF-1信号通路(HIF-1 signaling pathway)、AGE-RAGE信号通路在糖尿病并发症中的调控(AGE-RAGE signaling pathway in diabetic complications)、AMPK信号通路(AMPK signaling pathway)、非酒精性脂肪肝(Non-alcoholic fatty liver disease)、脂质与动脉粥样硬化(Lipid and atherosclerosis)等关键代谢途径。综合GO功能富集分析结果,山楂、荷叶和薏仁潜在降脂作用机制主要与机体调控脂质代谢相关基因的表达、细胞内的能量状态以及脂质代谢相关酶活性有关,以上均与高脂血症的发病机制有一定关联,表明山楂、荷叶和薏仁的潜在降脂靶点可通过作用多种复杂生物途径,达到协同降脂的效果。
为进一步探究活性成分、靶点和通路相互之间的关系,构建了“成分-靶点-通路”交互网络(黄色节点表示活性成分、红色节点代表信号通路、蓝色节点代表作用靶点),该网络包含28个潜在活性成分、38个降脂相关靶蛋白及10条富集信号通路(图11)。网络拓扑分析显示(表2),谷甾醇(MOL000359)、豆甾醇(MOL000449)和芸香苷(MOL000415)等成分具有较高的节点度(Degree值),提示这些化合物可能会是山楂-薏仁-荷叶复方发挥降脂作用的关键活性物质。同时,从图中可以看出,山楂、薏仁和荷叶中28个潜在降脂活性成分作用于38个降脂相关靶点,主要涉及参与调控脂质与动脉粥样硬化通路(hsa05417)、HIF-1信号通路(hsa04066)、流体剪切应力与动脉粥样硬化通路(hsa05418)、胰岛素抵抗(hsa04931)、PI3K-Akt信号通路(hsa04151)等多条与降脂相关的信号通路,从而形成多成分、多靶点、多通路的协同作用网络,实现调控脂质代谢相关酶活性、氧化应激、胰岛素抵抗、脂质生成等多方面调节糖脂代谢平衡,最终有效降低血脂水平[21]。
结合PPI网络和成分-靶点-通路分析,筛选出INS、ALB、IL6、TNF、AKT1五个关键靶点,可能是山楂、薏仁、荷叶干预高脂血症的核心作用位点。此外,豆甾醇(Stigmasterol)、谷甾醇(Sitosterol)、芸香苷(Rutin)等成分在网络中节点度值较高,提示其在降脂过程中起重要作用。为验证成分-靶点相互作用,采用Autodock分子对接技术分析关键活性成分与潜在靶点的结合能力,分子对接结合能如表3所示,同时,将表中结合能前三的对接结果进行了可视化分析,如图12所示。其中结合能结果显示,大部分结合能低于−5 kcal/mol(活性良好阈值)[42],其中谷甾醇与TNF的结合能最优(−11.09 kcal/mol),此外,豆甾醇也与ALB靶蛋白表现出较强的结合能力(−11.07 kcal/mol)。其中,图12(b)中,活性成分与Glu64残基的极性侧链形成了两个氢键,长度为2.1 Å和1.9 Å,表明二者之间存在较强的氢键作用。该结果验证了网络药理学的预测,从分子层面揭示了山楂、薏仁、荷叶多组分协同降脂的机制,为开发天然降脂功能食品提供了理论依据。
本文主要围绕八种药食同源植物水提液的降脂作用展开研究,重点探讨了山楂、荷叶和薏仁的降脂作用机制。从活性成分含量与降脂活性看,荷叶水提液的总黄酮、总酚含量显著高于其他样品(P<0.05),山楂水提液的总糖含量最高,且二者均表现出强抗氧化活性。在脂质代谢相关酶活抑制实验中,山楂对胰脂肪酶、α-葡萄糖苷酶和α-淀粉酶的抑制作用最强,荷叶次之,薏仁对胆固醇酯酶的抑制效果最显著;同时,山楂和荷叶在胆酸钠结合及胆固醇吸附试验中表现最优,进一步体现降脂潜力。主成分分析(PCA)表明,山楂与荷叶的降脂作用存在一定相似性,薏仁则通过特异性抑制胆固醇酯酶发挥显著降胆固醇作用。网络药理学分析从机制层面得出:三者的活性成分可能通过调控胰岛素抵抗、AGE-RAGE、AMPK等信号通路,干预脂质代谢和动脉粥样硬化等过程;同时参与酶结合、氧化还原酶活性调节等,通过多途径发挥降脂功效。分子对接结果显示,其关键成分(豆甾醇、谷甾醇和芸香苷)与核心靶点(INS、ALB、IL6等)结合能力强,为上述机制提供支撑。综上,山楂、荷叶和薏仁通过多靶点、多通路协同调节脂代谢,降脂潜力显著,有望成为降脂功能性食品开发的优先候选材料,为代谢综合征的膳食干预提供新策略。但本研究结论仅为基于网络药理学和分子对接的生物信息学预测,所得结论还需通过后续开展细胞水平功能实验、动物模型等进行进一步验证。

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2026年第47卷第11期
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doi: 10.13386/j.issn1002-0306.2025040227
  • 接收时间:2025-04-18
  • 首发时间:2026-10-22
  • 出版时间:2026-06-01
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  • 收稿日期:2025-04-18
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    1湖南农业大学食品科学技术学院,湖南长沙 410128
    2宁波大学食品科学与工程学院,浙江宁波 315211
    3赣南医科大学护理学院,江西赣州 341000

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肖愈(1989−),男,博士,副教授,研究方向:食品微生物与发酵食品,天然产物生物转化与活性评价,E-mail:。
孔文平(1992−),男,博士,讲师,研究方向:益生菌与药食同源产品开发,天然产物生物合成与活性评价,E-mail:。
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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