Article(id=1321170281255785342, tenantId=1146029695717560320, journalId=1260987677001138203, issueId=1321170163563614210, articleNumber=null, orderNo=null, doi=10.13386/j.issn1002-0306.2024120200, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734364800000, receivedDateStr=2024-12-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792921141208, onlineDateStr=2026-10-25, pubDate=1769875200000, pubDateStr=2026-02-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792921141208, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792921141208, creator=13701087609, updateTime=1792921141208, updator=13701087609, issue=Issue{id=1321170163563614210, tenantId=1146029695717560320, journalId=1260987677001138203, year='2026', volume='47', issue='3', pageStart='1', pageEnd='497', issueExtLink='null', onlineDate='null', pubDate='1769875200000', pubDateStr='2026-02-01', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792921113148, creator='13701087609', updateTime=1792921113148, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=207, endPage=220, ext={EN=ArticleExt(id=1321170281473889151, articleId=1321170281255785342, tenantId=1146029695717560320, journalId=1260987677001138203, language=EN, title=Process Optimization of Antioxidant Peptides Preparation from White Kidney Beans via Bacteria-Enzyme Synergy and Analysisof Their Antioxidant Activity, columnId=1261343843090313538, journalTitle=Science and Technology of Food Industry, columnName=Processing Technology, runingTitle=null, highlight=null, articleAbstract=

In this study, white kidney bean protein was utilized as a primary material to produce antioxidant peptides through a combined approach involving Bacillus subtilis fermentation and neutral protease treatment. The optimal processing conditions for peptide production were determined using single-factor experiments and response surface methodology, and the amino acid composition and the molecular weight distribution of the peptides were analyzed. Ultrafiltration was employed to isolate specific peptide fractions, and their antioxidant properties were assessed. The most promising antioxidant peptides were identified through liquid chromatography-tandem mass spectrometry (LC-MS/MS). Further investigation into the peptide's potential antioxidative properties was conducted through virtual screening, molecular docking, and molecular dynamics simulation. Results indicated that the ideal conditions for peptide formation were a fermentation temperature of 37.0 ℃, a fermentation period of 48.0 h, and an inoculum level of 5.0%. Under these conditions, the DPPH radical scavenging ability reached 76.12%±0.36%, and the peptide yield was 17.59%±0.16%. In WKBPs, the content of hydrophobic, basic, and acidic amino acids was relatively high, at 21.932%, 11.331%, and 20.583% respectively. The molecular weight distribution was predominantly below 3 kDa, and ultrafiltration showed that peptides with molecular weights under 3 kDa exhibited substantial antioxidant activity, as indicated by their DPPH, ABTS+, and hydroxyl radical scavenging rates, with IC50 values of 0.307, 0.310, and 0.361 mg/mL, respectively. The total antioxidant capacity was measured at 0.66±0.0018 mmol Fe2+/g at a concentration of 1 mg/mL. Among the 6364 peptide sequences analyzed, three active pentapeptides (FGWGP, FGHPEW and FGPYF) were identified, each forming a stable complex with Keap1 protein through hydrogen bonds and hydrophobic interactions. Molecular dynamics simulations indicated that these peptides could bind tightly to Keap1, forming stable conformations. This study provides both a technical guide and a theoretical foundation for further exploration and development of white kidney bean proteins and antioxidant peptide-based products.

, authors=Xiaoyan XIE1, Yunxi ZHANG1, Ying WANG1, 2, 3, *, Tong LIU1, Sinan LI4, Weiqiao PANG1, Zhaohang ZUO1, Lu ZHANG4, *, Xiao GUAN5, Zili ZHAO6, Bing LI6, authorsList=Xiaoyan XIE, Yunxi ZHANG, Ying WANG, Tong LIU, Sinan LI, Weiqiao PANG, Zhaohang ZUO, Lu ZHANG, Xiao GUAN, Zili ZHAO, Bing LI, authorCompany=null, correspAuthors=Ying WANG, Lu ZHANG, 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=1321170283206136720, articleId=1321170281255785342, tenantId=1146029695717560320, journalId=1260987677001138203, language=CN, title=菌-酶协同法制备白芸豆抗氧化肽工艺优化及其抗氧化活性分析, columnId=1261343845481066826, journalTitle=食品工业科技, columnName=工艺技术, runingTitle=null, highlight=null, articleAbstract=

为建立一种高效筛选白芸豆多肽(White kidney bean polypeptides,WKBPs)的方法并分析其体外抗氧化活性,本实验以白芸豆蛋白为原料,采用中性蛋白酶和枯草芽孢杆菌协同法制备WKBPs,通过单因素和响应面试验确定最佳工艺参数,并测定其氨基酸组成和相对分子质量分布,利用超滤技术对制备的白芸豆粗肽进行分级分离,测定不同组分的抗氧化活性,对活性最好的组分进行液相色谱-质谱联用(LC-MS/MS)检测,并利用虚拟筛选、分子对接技术及分子动力学模拟探究肽段的潜在抗氧化活性。结果显示:菌-酶协同法制备WKBPs最佳工艺参数为发酵温度37.0 ℃、发酵时间48.0 h、接种量5.0%,此条件下的DPPH自由基清除率为76.12%±0.36%,多肽得率为17.59%±0.16%;WKBPs中疏水性氨基酸、碱性氨基酸和酸性氨基酸含量均较高,分别为21.932%、11.331%和20.583%;相对分子质量分布主要集中在3 kDa以下,超滤结果表明Mw<3 kDa的组分具有较好的抗氧化活性(DPPH自由基清除率、ABTS+自由基清除率和羟自由基清除率),其半抑制浓度(IC50)值分别为0.307、0.310和0.361 mg/mL;总抗氧化能力(FRAP)在1 mg/mL的浓度下可以达到0.66±0.0018 mmol Fe2+/g;通过虚拟筛选从LC-MS/MS鉴定的6364条肽序列中得到3条抗氧化多肽(FGWGP、FGHPEW和FGPYF),分子对接结果表明:肽段能够通过氢键及疏水相互作用等与Keap1结合形成稳定的复合物,调控Keap1-Nrf2通路发挥抗氧化作用;分子动力学模拟表明,FGWGP、FGHPEW和FGPYF可以与Keap1紧密结合形成稳定的构象。本实验为白芸豆蛋白的深度开发和白芸豆抗氧化肽产品的研发提供技术参考及理论基础。

, authors=谢晓妍1, 张芸溪1, 王颖1, 2, 3, *, 刘童1, 李思楠4, 庞惟俏1, 佐兆杭1, 张璐4, *, 管骁5, 赵自力6, 李冰6, authorsList=谢晓妍, 张芸溪, 王颖, 刘童, 李思楠, 庞惟俏, 佐兆杭, 张璐, 管骁, 赵自力, 李冰, authorCompany=null, correspAuthors=王颖, 张璐, authorNote=

谢晓妍(2000−),女,硕士研究生,研究方向:粮食、油脂及植物蛋白工程,E-mail:

, correspAuthorsNote=
王颖(1979−),女,博士,教授,研究方向:农产品加工与贮藏工程及食品质量安全,E-mail:。
张璐(1987−),女,博士,高级工程师,研究方向:功能食品开发与精准营养及功效评价,E-mail:。
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谢晓妍(2000−),女,硕士研究生,研究方向:粮食、油脂及植物蛋白工程,E-mail:

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谢晓妍(2000−),女,硕士研究生,研究方向:粮食、油脂及植物蛋白工程,E-mail:

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注:图中不同字母表示组间差异显著(P<0.05),图4、图5同。

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注:(A)复合物的3D结构;(B)多肽和Keap1的静电表面;(C)复合物的详细结合模式;(D)多肽与Keap1活性位点相互作用的2D图,2D蓝色模型和红色扇区模型分别是肽和Keap1残基。

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Response surface test factors and levels of WKBPs prepared from fermented enzymatic solution

, figureFileSmall=null, figureFileBig=null, tableContent=
水平因素
A 发酵温度(℃)B 发酵时间(h)C 接种量(%)
−130363
037485
144607
), ArticleFig(id=1321170292005786615, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表1, caption=

发酵酶解液制备WKBPs响应面试验因素水平

, figureFileSmall=null, figureFileBig=null, tableContent=
水平因素
A 发酵温度(℃)B 发酵时间(h)C 接种量(%)
−130363
037485
144607
), ArticleFig(id=1321170292106449912, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 2, caption=

Response surface experimental design and test results

, figureFileSmall=null, figureFileBig=null, tableContent=
试验号ABCY综合值(%)
10−1−136.64
21100.00
300097.57
41−1034.39
5−1−108.68
610128.98
701−139.38
800096.77
900098.35
10−10132.81
11−10−141.28
12−11031.81
1300099.44
140−1140.47
1510−131.65
1601129.06
1700095.25
), ArticleFig(id=1321170292190335993, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表2, caption=

响应面试验方案与结果

, figureFileSmall=null, figureFileBig=null, tableContent=
试验号ABCY综合值(%)
10−1−136.64
21100.00
300097.57
41−1034.39
5−1−108.68
610128.98
701−139.38
800096.77
900098.35
10−10132.81
11−10−141.28
12−11031.81
1300099.44
140−1140.47
1510−131.65
1601129.06
1700095.25
), ArticleFig(id=1321170292244861946, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 3, caption=

Analysis of regression and variance results

, figureFileSmall=null, figureFileBig=null, tableContent=
变异来源平方和自由度均方F值P值显著性
模型18008.8292000.98686.74<0.0001极显著
A-发酵温度47.82147.8216.410.0049**
B-发酵时间49.65149.6517.040.0044**
C-接种量38.85138.8513.330.0082**
AB827.141827.14283.88<0.0001***
AC8.4118.412.890.1331
BC50.06150.0617.180.0043**
A26985.5816985.582397.48<0.0001***
B26087.7616087.762089.34<0.0001***
C22239.8312239.83768.72<0.0001***
残差20.4072.91
失拟项10.3133.441.360.3739不显著
纯误差10.0842.52
总离差18029.2216
), ArticleFig(id=1321170292328748027, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表3, caption=

回归与方差结果分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变异来源平方和自由度均方F值P值显著性
模型18008.8292000.98686.74<0.0001极显著
A-发酵温度47.82147.8216.410.0049**
B-发酵时间49.65149.6517.040.0044**
C-接种量38.85138.8513.330.0082**
AB827.141827.14283.88<0.0001***
AC8.4118.412.890.1331
BC50.06150.0617.180.0043**
A26985.5816985.582397.48<0.0001***
B26087.7616087.762089.34<0.0001***
C22239.8312239.83768.72<0.0001***
残差20.4072.91
失拟项10.3133.441.360.3739不显著
纯误差10.0842.52
总离差18029.2216
), ArticleFig(id=1321170292425217020, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 4, caption=

Analysis of amino acid composition (g/100 g)

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氨基酸种类含量(%)
天冬氨酸(Asp)7.920±0.025
苏氨酸(Thr)e2.583±0.009
丝氨酸(Ser)3.428±0.087
谷氨酸(Glu)12.663±0.010
甘氨酸(Gly)h2.673±0.012
丙氨酸(Ala)h2.316±0.008
缬氨酸(Val)eh3.026±0.066
半胱氨酸(Cys)0.170±0.003
蛋氨酸(Met)eh0.987±0.013
异亮氨酸(Ile)eh2.419±0.022
亮氨酸(Leu)eh4.023±0.146
酪氨酸(Tyr)2.300±0.010
苯丙氨酸(Phe)eh3.558±0.075
组氨酸(His)2.089±0.015
赖氨酸(Lys)e5.363±0.005
精氨酸(Arg)3.879±0.018
脯氨酸(Pro)h2.930±0.052
必需氨基酸21.959±0.123
疏水性氨基酸21.932±0.096
), ArticleFig(id=1321170292504908797, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表4, caption=

氨基酸组成成分分析(g/100 g)

, figureFileSmall=null, figureFileBig=null, tableContent=
氨基酸种类含量(%)
天冬氨酸(Asp)7.920±0.025
苏氨酸(Thr)e2.583±0.009
丝氨酸(Ser)3.428±0.087
谷氨酸(Glu)12.663±0.010
甘氨酸(Gly)h2.673±0.012
丙氨酸(Ala)h2.316±0.008
缬氨酸(Val)eh3.026±0.066
半胱氨酸(Cys)0.170±0.003
蛋氨酸(Met)eh0.987±0.013
异亮氨酸(Ile)eh2.419±0.022
亮氨酸(Leu)eh4.023±0.146
酪氨酸(Tyr)2.300±0.010
苯丙氨酸(Phe)eh3.558±0.075
组氨酸(His)2.089±0.015
赖氨酸(Lys)e5.363±0.005
精氨酸(Arg)3.879±0.018
脯氨酸(Pro)h2.930±0.052
必需氨基酸21.959±0.123
疏水性氨基酸21.932±0.096
), ArticleFig(id=1321170294165853182, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 5, caption=

Results of molecular mass distribution of WKBPs

, figureFileSmall=null, figureFileBig=null, tableContent=
分子量(Da)保留时间(min)相对含量(%)
>50006.40~8.007.50
3000~50008.01~8.467.50
<30008.46~15.0285.00
), ArticleFig(id=1321170294232962047, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表5, caption=

WKBPs分子质量分布结果

, figureFileSmall=null, figureFileBig=null, tableContent=
分子量(Da)保留时间(min)相对含量(%)
>50006.40~8.007.50
3000~50008.01~8.467.50
<30008.46~15.0285.00
), ArticleFig(id=1321170294308459520, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 6, caption=

IC50 of free radical clearance of WKBPs at different concentrations

, figureFileSmall=null, figureFileBig=null, tableContent=
类别白芸豆多肽(mg/mL)
DPPH自由基清除率0.307
ABTS+自由基清除率0.310
羟自由基清除率0.361
), ArticleFig(id=1321170294375567360, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表6, caption=

不同浓度WKBPs3的自由基清除率的IC50

, figureFileSmall=null, figureFileBig=null, tableContent=
类别白芸豆多肽(mg/mL)
DPPH自由基清除率0.307
ABTS+自由基清除率0.310
羟自由基清除率0.361
), ArticleFig(id=1321170294451064833, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=EN, label=Table 7, caption=

Virtual screening results of the peptide sequences identified by WKBPs3

, figureFileSmall=null, figureFileBig=null, tableContent=
肽段预测生物活性评分分子量(Da)结合能(kcal/mol)毒性疏水性氨基酸占比(%)自由基清除活性评分
FGWGP0.9874562.254−10.9Non1000.5852
FGHPEW0.8623771.334−10.8Non670.5757
FGPYF0.9905629.2849−10.7Non800.5810
LGPHW0.9030819.4028−10.6Non800.5854
FSHPGDF0.9182805.3395−10.3Non570.5327
FGALGHGL0.7283770.4075−10.2Non870.5166
FEGNWGPL0.8890918.4235−10.1Non750.5849
FYPFPHP0.9506903.4279−10.0Non710.6363
PGPGY0.8566489.2223−10.0Non400.5700
LGGGWPEM0.7222845.374−10.0Non500.5892
), ArticleFig(id=1321170294539145218, tenantId=1146029695717560320, journalId=1260987677001138203, articleId=1321170281255785342, language=CN, label=表7, caption=

WKBPs3鉴定得到的肽序列的虚拟筛选结果

, figureFileSmall=null, figureFileBig=null, tableContent=
肽段预测生物活性评分分子量(Da)结合能(kcal/mol)毒性疏水性氨基酸占比(%)自由基清除活性评分
FGWGP0.9874562.254−10.9Non1000.5852
FGHPEW0.8623771.334−10.8Non670.5757
FGPYF0.9905629.2849−10.7Non800.5810
LGPHW0.9030819.4028−10.6Non800.5854
FSHPGDF0.9182805.3395−10.3Non570.5327
FGALGHGL0.7283770.4075−10.2Non870.5166
FEGNWGPL0.8890918.4235−10.1Non750.5849
FYPFPHP0.9506903.4279−10.0Non710.6363
PGPGY0.8566489.2223−10.0Non400.5700
LGGGWPEM0.7222845.374−10.0Non500.5892
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菌-酶协同法制备白芸豆抗氧化肽工艺优化及其抗氧化活性分析
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谢晓妍 1 , 张芸溪 1 , 王颖 1, 2, 3, * , 刘童 1 , 李思楠 4 , 庞惟俏 1 , 佐兆杭 1 , 张璐 4, * , 管骁 5 , 赵自力 6 , 李冰 6
食品工业科技 | 工艺技术 2026,47(3): 207-220
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食品工业科技 |工艺技术 2026 , 47 (3) : 207 -220
菌-酶协同法制备白芸豆抗氧化肽工艺优化及其抗氧化活性分析
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谢晓妍(2000−),女,硕士研究生,研究方向:粮食、油脂及植物蛋白工程,E-mail:

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谢晓妍1 , 张芸溪1, 王颖1, 2, 3, * , 刘童1, 李思楠4, 庞惟俏1, 佐兆杭1, 张璐4, * , 管骁5, 赵自力6, 李冰6
作者信息
  • 1黑龙江八一农垦大学食品学院,黑龙江大庆 163319
  • 2国家杂粮工程技术中心,黑龙江大庆 163319
  • 3厦门海洋职业技术学院,福建厦门 361100
  • 4中国食品发酵工业研究院有限公司,功能主食创制与慢病营养干预北京市重点实验室,北京 100015
  • 5上海理工大学健康科学与工程学院,上海 200093
  • 6安徽省农业科学院皖北研究院,安徽阜阳 236600
通讯作者:
王颖(1979−),女,博士,教授,研究方向:农产品加工与贮藏工程及食品质量安全,E-mail:。
张璐(1987−),女,博士,高级工程师,研究方向:功能食品开发与精准营养及功效评价,E-mail:。
作者简介:

谢晓妍(2000−),女,硕士研究生,研究方向:粮食、油脂及植物蛋白工程,E-mail:

Process Optimization of Antioxidant Peptides Preparation from White Kidney Beans via Bacteria-Enzyme Synergy and Analysisof Their Antioxidant Activity
Xiaoyan XIE1 , Yunxi ZHANG1, Ying WANG1, 2, 3, * , Tong LIU1, Sinan LI4, Weiqiao PANG1, Zhaohang ZUO1, Lu ZHANG4, * , Xiao GUAN5, Zili ZHAO6, Bing LI6
Affiliations
  • 1College of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, China
  • 2National Coarse Cereals Engineering Center, Daqing 163319, China
  • 3Xiamen Ocean Vocational College, Xiamen 361100, China
  • 4China National Research Institute of Food and Fermentation Industries Co., Ltd., Beijing Key Laboratory of the Innovative Development of Functional Staple and the Nutritional Intervention for Chronic Disease, Beijing 100015, China
  • 5School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 6Anhui Academy of Agricultural Sciences Wanbei Research Institute, Fuyang 236600, China
出版时间: 2026-02-01 doi: 10.13386/j.issn1002-0306.2024120200
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为建立一种高效筛选白芸豆多肽(White kidney bean polypeptides,WKBPs)的方法并分析其体外抗氧化活性,本实验以白芸豆蛋白为原料,采用中性蛋白酶和枯草芽孢杆菌协同法制备WKBPs,通过单因素和响应面试验确定最佳工艺参数,并测定其氨基酸组成和相对分子质量分布,利用超滤技术对制备的白芸豆粗肽进行分级分离,测定不同组分的抗氧化活性,对活性最好的组分进行液相色谱-质谱联用(LC-MS/MS)检测,并利用虚拟筛选、分子对接技术及分子动力学模拟探究肽段的潜在抗氧化活性。结果显示:菌-酶协同法制备WKBPs最佳工艺参数为发酵温度37.0 ℃、发酵时间48.0 h、接种量5.0%,此条件下的DPPH自由基清除率为76.12%±0.36%,多肽得率为17.59%±0.16%;WKBPs中疏水性氨基酸、碱性氨基酸和酸性氨基酸含量均较高,分别为21.932%、11.331%和20.583%;相对分子质量分布主要集中在3 kDa以下,超滤结果表明Mw<3 kDa的组分具有较好的抗氧化活性(DPPH自由基清除率、ABTS+自由基清除率和羟自由基清除率),其半抑制浓度(IC50)值分别为0.307、0.310和0.361 mg/mL;总抗氧化能力(FRAP)在1 mg/mL的浓度下可以达到0.66±0.0018 mmol Fe2+/g;通过虚拟筛选从LC-MS/MS鉴定的6364条肽序列中得到3条抗氧化多肽(FGWGP、FGHPEW和FGPYF),分子对接结果表明:肽段能够通过氢键及疏水相互作用等与Keap1结合形成稳定的复合物,调控Keap1-Nrf2通路发挥抗氧化作用;分子动力学模拟表明,FGWGP、FGHPEW和FGPYF可以与Keap1紧密结合形成稳定的构象。本实验为白芸豆蛋白的深度开发和白芸豆抗氧化肽产品的研发提供技术参考及理论基础。

白芸豆多肽  /  菌-酶协同  /  超滤  /  抗氧化活性  /  分子对接

In this study, white kidney bean protein was utilized as a primary material to produce antioxidant peptides through a combined approach involving Bacillus subtilis fermentation and neutral protease treatment. The optimal processing conditions for peptide production were determined using single-factor experiments and response surface methodology, and the amino acid composition and the molecular weight distribution of the peptides were analyzed. Ultrafiltration was employed to isolate specific peptide fractions, and their antioxidant properties were assessed. The most promising antioxidant peptides were identified through liquid chromatography-tandem mass spectrometry (LC-MS/MS). Further investigation into the peptide's potential antioxidative properties was conducted through virtual screening, molecular docking, and molecular dynamics simulation. Results indicated that the ideal conditions for peptide formation were a fermentation temperature of 37.0 ℃, a fermentation period of 48.0 h, and an inoculum level of 5.0%. Under these conditions, the DPPH radical scavenging ability reached 76.12%±0.36%, and the peptide yield was 17.59%±0.16%. In WKBPs, the content of hydrophobic, basic, and acidic amino acids was relatively high, at 21.932%, 11.331%, and 20.583% respectively. The molecular weight distribution was predominantly below 3 kDa, and ultrafiltration showed that peptides with molecular weights under 3 kDa exhibited substantial antioxidant activity, as indicated by their DPPH, ABTS+, and hydroxyl radical scavenging rates, with IC50 values of 0.307, 0.310, and 0.361 mg/mL, respectively. The total antioxidant capacity was measured at 0.66±0.0018 mmol Fe2+/g at a concentration of 1 mg/mL. Among the 6364 peptide sequences analyzed, three active pentapeptides (FGWGP, FGHPEW and FGPYF) were identified, each forming a stable complex with Keap1 protein through hydrogen bonds and hydrophobic interactions. Molecular dynamics simulations indicated that these peptides could bind tightly to Keap1, forming stable conformations. This study provides both a technical guide and a theoretical foundation for further exploration and development of white kidney bean proteins and antioxidant peptide-based products.

white kidney bean polypeptide  /  bacteria-enzyme synergy  /  ultrafiltration  /  antioxidant activity  /  molecular docking
谢晓妍, 张芸溪, 王颖, 刘童, 李思楠, 庞惟俏, 佐兆杭, 张璐, 管骁, 赵自力, 李冰. 菌-酶协同法制备白芸豆抗氧化肽工艺优化及其抗氧化活性分析. 食品工业科技, 2026 , 47 (3) : 207 -220 . DOI: 10.13386/j.issn1002-0306.2024120200
Xiaoyan XIE, Yunxi ZHANG, Ying WANG, Tong LIU, Sinan LI, Weiqiao PANG, Zhaohang ZUO, Lu ZHANG, Xiao GUAN, Zili ZHAO, Bing LI. Process Optimization of Antioxidant Peptides Preparation from White Kidney Beans via Bacteria-Enzyme Synergy and Analysisof Their Antioxidant Activity[J]. Science and Technology of Food Industry, 2026 , 47 (3) : 207 -220 . DOI: 10.13386/j.issn1002-0306.2024120200
氧化应激是机体内一种氧化还原失衡的状态[1],由于机体受到环境等各方面的影响,会产生过量的自由基催生氧化应激反应,造成细胞凋亡[2]和DNA损伤[3],进而引发一系列疾病,如糖尿病、心血管疾病和癌症等[4−5]。传统合成的抗氧化剂虽效果显著,但潜在的毒副作用和生物利用度问题限制了其应用[6],因此,寻找天然有效的抗氧化剂显得尤为重要。抗氧化肽作为一种新型的抗氧化剂,因其显著的抗氧化活性、安全性和易于吸收等特点,受到了广泛的关注和研究[7]。白芸豆(Phaseolus vulgaris L.)是一种富含优质植物蛋白的豆类资源,芸豆蛋白富含人体所需的所有必需氨基酸,其总必需氨基酸含量优于大豆,是一种制备生物活性肽的优质植物原料[8−9]。
近年来,酶解法和微生物发酵法被广泛用于生物活性肽的制备,但单一的酶解易产生苦味且酶解位点单一限制了活性肽的功能活性[10],而微生物发酵法存在发酵周期长、产物复杂且不易控制等问题[11]。通过菌-酶协同法将酶解与发酵相结合,可以实现优势互补,首先利用酶解法高效切割蛋白质的特定肽键,将大分子蛋白分解为中等大小的肽段,然后通过微生物发酵进一步分解这些肽段,可以产生更多具备活性的小分子肽[12]。臧凤[13]利用酶解得到蛋清酶解物后继续通过乳酸菌发酵协同制备蛋清肽得到了更高活性的抗氧化肽,经菌-酶协同发酵制得的蛋清酶解肽FRAP值是未发酵的4.65倍;马慧等[14]利用枯草芽孢杆菌和碱性蛋白酶协同固态发酵制备核桃谷蛋白抑菌肽,多肽含量达到26.35±1.29 mg/g;Fan等[15]通过添加淀粉酶和脂肪酶辅助枯草芽孢杆菌、鼠李糖乳杆菌、保加利亚乳杆菌等菌株发酵制备藜麦多肽,结果表明酶-菌协同法制备的藜麦肽比单一酶解法制备的多肽具有更强的ACE抑制活性。以上研究结果表明,菌-酶协同法可以显著提高多肽的产量和活性。
随着生物信息学的飞速发展,计算机模拟技术在抗氧化肽的筛选中展现出了巨大的潜力[16],徐斐然等[17]利用计算机分析技术和分子模拟技术从宁夏肉牛血红蛋白中高效筛选出两条新型抗氧化肽VFYPW和DGWHS。Yu等[18]采用体外和计算机相结合的方法从豆粕中鉴定出一种新的抗氧化肽(KFGW),研究显示KFGW可通过氢键和范德华相互作用占据Keap1上的Nrf2结合位点来有效激活Keap1-Nrf2-HO-1通路。以上研究结果表明,分子对接技术已成为用于筛选抗氧化肽的重要工具,并且在分子水平上揭示了抗氧化肽与靶标间的作用机制。
目前,虽然有大量研究报道了芸豆多肽在降血压、抗肿瘤等方面的生物活性及其作用机理,但有关采用菌-酶协同法制备白芸豆多肽及其抗氧化活性和分子构效研究甚少。因此,本实验以白芸豆为原料,通过菌-酶协同法制备WKBPs,并优化其工艺参数,以期获得高活性、高得率的WKBPs。同时,通过氨基酸组成分析、相对分子质量分布、超滤组分分离及其抗氧化活性测定等手段,对WKBPs的理化性质和抗氧化活性进行评价。此外,利用LC-MS/MS质谱鉴定肽序列结合虚拟筛选和分子对接技术评估肽段的潜在抗氧化活性,以期为白芸豆健康产品的开发提供新的思路。
白芸豆 林家粮铺,产自黑龙江省;枯草芽孢杆菌(Bacillus subtilis) 中国工业微生物菌种保藏中心;LB肉汤培养基、琼脂 海博生物技术有限公司;中性蛋白酶(50 U/mg) 北京Solarbio生物科技有限公司;三氯乙酸、VC 上海麦克林生化科技有限公司;2,2'-联氮-双-3-乙基苯并噻唑啉-6-磺酸(ABTS)、2,4,6-三吡啶基三嗪(TPTZ)、1,1-二苯基-2-三硝基苯肼(DPPH)、Gly-Gly-Gly(189 Da)、Gly-Gly-Tyr-Arg(451 Da)、杆菌肽(1423 Da)、胰岛素(5778 Da)、细胞色素C(12384 Da) 美国Sigma公司;双缩脲试剂(AB液)、硫酸亚铁(FeSO4)、水杨酸 上海源叶生物科技有限公司。
CHRIST真空冷冻干燥机 德国Christ公司;YXQ-100G高温高压灭菌锅 上海博迅医疗生物仪器有限公司;DL-CL-2ND超净工作台 哈东联电子技术有限公司;DNP-9052恒温培养箱 上海精宏实验设备公司;HZQ-A恒温摇床 常州市科迈实验仪器有限公司;U-2910紫外可见分光光度计 日本Hitachi公司;GL21M高速冷冻离心机 湖南湘仪有限公司;LA8080超高速全自动氨基酸分析仪 广州市君翔仪器仪表有限公司;Cf72-8YW酶联免疫检测仪 珀金埃尔默仪器有限公司;Waters1525高效液相色谱仪 美国Waters公司;Q Exactive Plius质谱仪 美国赛默飞世尔有限公司。
参照周雅情等[19]的方法并稍作修改,白芸豆洗净60 ℃烘干后粉碎,过80目筛,用石油醚按液料比10 mL/g脱脂后得到脱脂白芸豆粉,将脱脂白芸豆粉用蒸馏水以液料比10 mL/g的比例混合,调节pH至8.5后,50 ℃搅拌1 h,离心(4000 r/min,10 min),取上清液调节pH至4.4,4 ℃搅拌2 h后离心(4000 r/min,10 min)收集沉淀,冷冻干燥后得白芸豆蛋白粉(纯度为89%,−80 ℃保存)。
将保藏的枯草芽孢杆菌菌液1 mL转接到LB液体培养基中恒温培养(37 ℃,24 h),后划线接入LB固体培养基中恒温培养(37 ℃,24 h),使其充分活化。挑取一环单菌落移至LB液体培养基中恒温培养(37 ℃,24 h),得到扩大培养的枯草芽孢杆菌菌悬液,用平板计数法计数调整含活菌数为1.0×107 CFU/mL用于以下实验。
准确称取白芸豆蛋白5.0 g加入100.0 mL去离子水溶解,添加3000 U/g中性蛋白酶于53 ℃、pH为7条件下酶解2 h,121 ℃灭菌灭酶15 min进行后续发酵。加入5%枯草芽孢杆菌种子液,37 ℃下发酵48 h,发酵完毕后离心(4000 r/min,15 min)收集上清液冷冻干燥,得到白芸豆多肽粗提物。
通过枯草芽孢杆菌发酵白芸豆蛋白酶解液制备WKBPs,以多肽得率和DPPH自由基清除率为指标,分别固定发酵温度、发酵时间、接种量为37 ℃、48 h、5%,考察发酵温度(23、30、37、44、51 ℃),发酵时间(12、24、36、48、60 h),接种量(1%、3%、5%、7%、9%)对制备WKBPs的影响。
根据Box-Behnken设计原理,结合单因素实验结果,选择发酵温度(A)、发酵时间(B)和接种量(C)3个因素设计三因素三水平试验,以综合值(Y)为响应值,应用Design-Expert 13.0.5进行优化试验,各因素水平见表1。
在优化条件下重复3次实验,测定多肽得率和DPPH自由基清除率,以验证优化实验条件的准确性与稳定性。
参考刘潇[20]的方法,取2 mL WKBPs粗提液加入2 mL 10%三氯乙酸(TCA)反应10 min后离心(4000 r/min,10 min),上清液稀释10倍后取1 mL稀释液与4 mL双缩脲试剂混合均匀,室温反应30 min,测定540 nm处OD值,以Gly-Gly-Tyr-Arg四肽为标准品绘制标准曲线,得到回归方程为:y=0.0626x+0.0526,R2=0.999。对照标准曲线计算样品溶液中的多肽含量,按公式(1)计算WKBPs的得率。
$ \rm{得率}({\text{%}})=\frac{C\times V}{m}\times 100 $
式中:C—溶液中多肽浓度(mg/mL);V—溶液总体积(mL);m—白芸豆蛋白质质量(mg)。
参考Sun等[21]方法,将WKBPs粗提液与0.1 mmol/L DPPH-乙醇溶液按1:1混合后暗反应(25 ℃,30 min),在517 nm处测定OD值,根据公式(2)计算。
$ \rm{P}({\text{%}})=\left(1-\frac{{A}_{i}-{A}_{j}}{{A}_{k}}\right)\times 100 $
式中:P—自由基清除率;Ai—样品与DPPH溶液混合液的吸光度;Aj—样品与无水乙醇溶液混合液的吸光度;Ak—DPPH溶液与无水乙醇溶液混合液的吸光度。
将多肽得率和DPPH自由基清除率数据分别标准化为0~1间的归一值。二者权重均为50%,归一值OD计算如公式(3),综合值(Y)计算如公式(4)[22]。
$ \mathrm{O}\mathrm{D}=\frac{{\mathrm{D}}_{\mathrm{i}}-{\mathrm{D}}_{\mathrm{m}\mathrm{i}\mathrm{n}}}{{\mathrm{D}}_{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{D}}_{\mathrm{m}\mathrm{i}\mathrm{n}}} $
式中:Di—当前实验值;Dmin—同组实验中最小值;Dmax—同组实验中最大值。
$ \rm{Y}={\mathrm{O}\mathrm{D}}_{1}\times 50{\text{%}}+{\mathrm{O}\mathrm{D}}_{2}\times 50{\text{%}} $
式中:OD1—多肽得率归一值;OD2—DPPH自由基清除率归一值。
根据GB 5009.124-2016《食品中氨基酸的测定》,选用茚三酮法测定WKBPs的游离氨基酸含量,以L-亮氨酸为标准品,绘制标准曲线。
参考李思楠等[23]方法稍作修改。使用高效液相凝胶渗透色谱法(GPC)分析WKBPs的分子质量分布,色谱柱为TSKgelG2000SWXL(300 nm×7.8 nm),流速为0.3 mL/min,柱温为25 ℃,检测波长为220 nm,流动相为20%乙腈+80%去离子水+0.1%三氟乙酸,采用Gly-Gly-Gly、Gly-Gly-Tyr-Arg、杆菌肽、胰岛素和细胞色素C为校正标准品,用GPC软件对色谱数据进行处理,计算WKBPs的相对分子质量和分布情况。
用不同超滤膜(3 kDa、5 kDa)的超滤管对前期制备的WKBPs粗肽进行分级分离,按分子量大小分为WKBPs1(Mw>5 kDa)、WKBPs2(3 kDa<Mw<5 kDa)、WKBPs3(Mw<3 kDa)三个组分,将三个组分收集浓缩并冷冻干燥,蒸馏水复溶配制成1 mg/mL,通过测定体外抗氧化活性筛选最佳组分。
按1.2.8中方法对1 mg/mL WKBPs1、WKBPs2、WKBPs3样品进行测定。
参考沙玉欢等[24]方法,取1.4 mL稀释后的ABTS工作液分别与0.1 mL 1 mg/mL WKBPs1、WKBPs2、WKBPs3溶液混匀,避光反应(25 ℃,6 min),测定734 nm处OD值,计算如公式(2)。
参考夏吉安等[25]方法,将1 mg/mL WKBPs1、WKBPs2、WKBPs3溶液分别与FeSO4·7H2O溶液(6 mmol/L)和H2O2溶液(6 mmol/L)按1:1:1的体积比混匀后反应(37 ℃,10 min),接着向反应体系中加入1 mL水杨酸溶液(6 mmol/L),并充分混合,继续孵育(37 ℃,30 min),测定510 nm处OD值,计算如公式(2)。
参考卢跃红等[26]方法。取0.1 mL 1 mg/mL WKBPs1、WKBPs2、WKBPs3溶液和0.5 mL FRAP试剂混合均匀后,37 ℃反应10 min,测定595 nm处OD值,铁离子还原能力以FeSO4当量表示。FeSO4标准曲线回归方程为:y=0.219x−0.0008,R2=0.9995。
运用串联 EASY-nanoLC 1200的Orbitrap Q-Exactive Plus质谱仪对WKBPs3序列进行精确鉴定。使用Acclaim PepMap C18(75 μm×25 cm)色谱柱,上样量为1 μL进行梯度分离,色谱柱流速设置为300 nL/min,柱温为40 ℃,电喷雾电压2 kV,检测波长220 nm。流动相:A为0.1%甲酸;B为80%乙腈+0.1%甲酸。梯度洗脱:B相在47 min以非线性梯度升至35%,在1 min内上升到100%,并维持12 min。一级质谱:扫描范围(m/z)处于200~2000,分辨率达70000,AGC target为3e6,最大注入时间为50 ms;二级质谱:分辨率为17500,AGC target为1e5,最大注入时间为45 ms,碰撞能量分别为28%、35%、48%,动态排除时间30 s。通过PEAKS Studio version 10.6(Bioinformatics Solutions Inc,Waterloo,Canada)对质谱数据进行分析。
将LC-MS/MS鉴定得到的肽段通过在线工具PeptideRanker(http://distilldeep.ucd.ie/PeptideRanker/)进行潜在生物活性预测评分,评分越高代表所预测肽可能具有的生物活性越强,并采用在线工具ToxinPred(http://crdd.osdd.net/raghava/toxinpred/)预测肽段毒性。采用AnOxPePred数据库(https://services.healthtech.dtu.dk/services/AnOxPePred-1.0/)预测肽段的自由基清除能力。
从RCSB数据库(www.rcsb.org)中获取Keap1蛋白的天然晶体结构(PDB ID:2FLU),采用AutoDocktools进行加氢、计算电荷等预处理,使用Chemdraw软件绘制多肽3D结构,并进行能量优化,利用PyRx(https://pyrx.sourceforge.io)软件计算对接能,选择配体在蛋白质结合口袋中结合能最低的对接模型作为最佳模型,采用AutoDock Vina1.1.2进行对接,使用Vina评分作为预测肽与Keap1结合的亲和力(以kcal/mol计算),采用Pymol2.1软件对肽段和Keap1的结合作用可视化。
使用Gromacs 2022对复合物进行100 ns MD模拟。蛋白质采用CHARMM 36力场参数,配体拓扑结构由GAFF2力场参数构建。采用周期性边界条件,将蛋白质-配体复合物放置在立方盒中。采用TIP3P水模型将水分子填充到盒子中,形成周期边界为1.2 nm的水盒。使用粒子网格Ewald(PME)和Verlet算法分别处理静电相互作用。随后进行100000步的等温等容系综平衡和等温等压系综平衡,耦合常数为0.1 ps,持续时间为100 ps模拟。范德华和库仑相互作用均使用1.0 nm的截止值计算。最后,系统在恒定温度(310 K)和恒压(1 bar)下利用Gromacs 2022进行分子动力学模拟。
采用Origin 2022软件进行制图及Design-Expert 13.0.5.0软件和Box-Behnken试验方法设计响应面优化分析。利用IBM SPSS statistics 21.0软件进行ANOVA显著性分析。每个样品均做3个平行,结果以平均值±标准误差表示。
DPPH是一种稳定的氮中心自由基,抗氧化肽通过活性基团(如酚羟基、巯基)的供氢/供电子作用,可以直接中和自由基,终止自由基链式反应[27]。此外,DPPH自由基清除率具有高度的稳定性和灵敏度,更易于量化和标准化[28],因此成为评价抗氧化活性的核心指标。由图1(A)可以看出,随发酵温度的升高,多肽得率呈现先增加后下降的趋势。当发酵温度为37 ℃时,多肽得率和DPPH自由基清除率最高,达到17.73%±0.27%和76.58%±0.41%。随后,随着温度的升高,多肽得率显著下降(P<0.05)。这可能是由于在发酵过程中,适度温度有利于枯草芽孢杆菌的生长繁殖,增加蛋白酶的分泌,但是高温会影响菌体的生长[29],因此,选择发酵温度为37 ℃进行后续实验。
由图1(B)可以看出,多肽得率和DPPH自由基清除率随发酵时间的增加先显著升高(P<0.05),在48 h达到峰值17.09%±0.24%和75.09%±0.39%,之后显著下降(P<0.05)。可能由于酶解液中含有大量肽段,发酵加快了多肽的生成,继续发酵可能会导致多肽被进一步水解成游离氨基酸,从而使多肽得率下降,并导致其抗氧化能力的降低[30]。因此,选择发酵时间为48 h进行后续实验。
由图1(C)可以看出,当接种量在5%(v/v)时多肽得率和DPPH自由基清除率达到最大值16.17%±0.20%和75.32%±0.31%。此后,随着接种量的增加,抗氧化活性显著降低(P<0.05),可能是微生物增多消耗了酶解液中的多肽,从而造成多肽得率的降低[31]。因此,选择接种量为5%进行后续实验。
用Design Expert 13.0.5.0软件对表2的试验数据进行回归与方差分析后,得到菌酶分步发酵制备WKBPs的综合值(Y)对A、B、C各因素变量的二次多元回归方程为:Y=97.48−2.45A−2.49B−2.20C−14.38AB+1.45AC−3.54BC−40.73A2−38.02B2−23.06C2。
从表3可知,对于综合值来说,模型F值为686.74(P<0.0001),说明该模型极显著。失拟项P=0.3739>0.05不显著,说明模型比较稳定,拟合度良好。其中,R2=0.9989,说明试验值和拟合值相关性较好,模型校正系数R2adj=0.9974,说明该模型能够解释99.74%试验数据响应值的变化。除AC外均达到极显著水平(P<0.01),说明三个因素对WKBPs的综合值均具有显著影响,因此,该二次回归方程可以客观预测发酵酶解液后综合值随各因素变化的规律。
菌-酶协同法制备WKBPs各个因素之间交互作用对综合值的影响如图2所示,B与A、C两两交互作用的响应面坡度变化较陡,等高线为椭圆形,说明对综合值均有显著影响,而B对应的响应面曲线及等高线变化相对陡峭,可以推知发酵时间对综合值的影响较大。
采用Design-Expert 13.0.5对试验优化分析,得到WKBPs最佳制备工艺为:发酵温度36.81 ℃、发酵时间47.69 h、接种量4.91%,此时综合值预测值为97.59%,DPPH自由基清除率为75.68%,多肽得率为17.46%。从实际操作性及节约资源方面,将菌酶分步发酵条件调整为发酵温度37 ℃、发酵时间48 h、接种量5%。在此条件下经过验证试验,DPPH自由基清除率为76.12%±0.36%,多肽得率为17.59%±0.16%。
氨基酸是生物活性肽的基本组成单位,氨基酸组成及含量在抗氧化活性中发挥着重要作用[32]。根据表4可知,WKBPs共检测出17种氨基酸(由于采用酸水解法检测,因此未检测出色氨酸),其中必需氨基酸有7种,含量为21.959%,其组成较为接近人体必需氨基酸模型。从氨基酸分布来看,碱性氨基酸总含量为11.331%,有助于肽在体内的运输和吸收[33];疏水性氨基酸含量高达21.932%,研究表明,疏水性氨基酸可使活性肽具有更高的抗氧化活性[34],原因可能是疏水侧链可促进抗氧化肽的富集,从而更高效地清除自由基[35];此外,WKBPs中还含有一定量的His和Tyr等具有特殊功能的氨基酸,它们可能通过各自的生物活性,共同参与到抗氧化过程中。综上表明,高含量疏水性氨基酸的存在使得WKBPs具有较高的抗氧化活性。
研究表明,小分子肽更容易被吸收到达靶位点,有效地发挥抗氧化活性[36]。WKBPs分子量分布谱图如图3所示,吸光度(AU)峰值集中在6.40~15.02 min内,主峰在约10~11 min处,表明WKBPs活性肽段主要集中在这一峰,分子量分布呈现出相对的均匀性,且纯度较高。此外,12.5~15 min出现的小峰和波动进一步提示存在游离氨基酸。各组分详细信息见表5,根据GPC数据分析软件计算可知Mw>5 kDa的肽段含量为7.50%、3 kDa<Mw<5 kDa的肽段含量为7.50%、Mw<3 kDa的肽段含量高达85.00%,表明WKBPs分子量主要集中在3 kDa以下,产物处于2~10肽间的活性低聚肽含量较高。现有研究表明,分子量小于3 kDa的低聚肽具有较好的抗氧化活性,活性基团更容易暴露于分子外部,易与结合位点相互作用[37]。李思涵等[38]的研究也表明分子量小于3 kDa的纳豆肽组分抗氧化能力最强。因此,推测制备的WKBPs具有较好的抗氧化作用。
生物活性肽的分子量大小是决定其生物特性的关键因素之一,较小分子量的肽通常具有较高的生物活性[39]。超滤是一种压力驱动的分离技术,可以将水解产物以分子量为基础分离成多种组分[40]。本实验将WKBPs经超滤后按分子量大小分为3个组分,以1 mg/mL浓度进行抗氧化活性测定,结果如图4所示,各组分均有抗氧化活性,且分子量的大小与抗氧化活性呈现出相关性,WKBPs3组分抗氧化能力显著高于其它组分(P<0.05),DPPH自由基清除率、ABTS+自由基清除率、羟自由基清除率和总抗氧化能力分别为79.05%±0.43%、91.82%±0.19%、94.30%±0.78%、0.7192±0.0053 mmol Fe2+/g,结果与朱巧楠等[41]结论相符,他们对油茶饼粕抗氧化肽超滤分离后发现分子量小于3 kDa的组分抗氧化活性最强。这可能是由于相对分子量小的肽具有较多的活性基团与自由基发生反应促使其转化为更加稳定的物质,表现出更好的自由基清除能力,并且可以提供更多的电子,相比于大分子量肽其更容易结合活性位点[42]。吴绍珍[43]也报道了分子量小于3 kDa的山核桃肽组分抗氧化能力最高。因此,综合考虑选择WKBPs3进行后续实验。
活性氧产生过多或抗氧化防御机制调控不足,会产生大量自由基,这些自由基会催生氧化应激反应[44]。本研究以0.1 g/mL VC为阳性对照,通过测定DPPH自由基清除率、ABTS+自由基清除率、羟自由基清除率和总抗氧化能力评估WKBPs3的抗氧化能力,结果如图5所示。从图5(A~C)可以看出,随着WKBPs3浓度的增加,其自由基清除能力呈上升趋势,且逐渐接近VC的清除率,其半抑制浓度(IC50)如表6,DPPH自由基清除率、ABTS+自由基清除率、羟自由基清除率IC50分别为0.307、0.310和0.361 mg/mL,结果表明WKBPs具有较好的自由基清除能力,这一结果与杨涵[45]制备的大豆肽自由基清除能力接近,这可能是由于WKBPs3存在较多的活性氨基酸残基,保持高氧化还原电位,为自由基提供有效的电子供体[46]。从图5(D)可以看出,WKBPs3在0.2~1.0 mg/mL浓度范围内,总抗氧化能力随WKBPs3浓度的增加而增加,在1 mg/mL的浓度下可以达到0.66±0.0018 mmol Fe2+/g,略低于VC,表现出较好的还原能力,与Cao等[47]对红豆肽总抗氧化能力的研究结果相似,可能是由于分子量较小的肽段其空间位阻较小,更易与金属离子形成配位化合物,使其金属离子螯合能力较强[48],以上结果说明WKBPs3具有较好的抗氧化活性,且呈现出剂量依赖性。
经LC-MS/MS氨基酸序列检测,从WKBPs3组分中共鉴定出6364条白芸豆源多肽序列,其一级质谱图如图6所示。肽段长度主要分布在3~18个氨基酸残基间,肽序列长度位于3~10的有4186条,占比65.78%,8肽占比最多为10%。其中,肽段中含有大量的亮氨酸、缬氨酸、苯丙氨酸等疏水性氨基酸及芳香族氨基酸,使其具有良好的抗氧化活性。
将鉴定出的肽段在PeptideRanker网站中进行潜在生物活性预测评分,筛选出得分大于0.7的肽段有677条,后进一步采用PyRx软件对其进行初步筛选,对结合能小于−10 kcal/mol肽段进行毒性、自由基清除活性预测,最终得到10条肽段,结果如表7所示。
Keap1蛋白是一种BTB-Kelch底物衔接蛋白,可调节Nrf2(一种bZIP转录因子)的稳态水平以响应氧化应激[49],据报道Keap1-Nrf2通路是消除体内氧化应激的最可能机制[50]。因此,进一步从分子水平上将鉴定出的肽段与Keap1蛋白进行结合,分析其相互作用力及结合位点等信息。研究表明,结合能越低,与靶标蛋白的相互作用越强[51],利用PyMol软件对FGWGP、FGHPEW和FGPYF与Keap1结合进行可视化处理,3D和2D分子相互作用如图7所示,FGWGP多肽能够与Keap1蛋白活性位点氨基酸残基Tyr334、Ser602、Tyr572和Gln530形成氢键相互作用,与Phe478和Tyr525形成疏水相互作用,与Arg415和Arg483提供部分疏水相互作用并同时辅助形成静电相互作用;FGHPEW多肽能够与氨基酸残基Arg483、Ser555、Arg380、Arg415形成氢键相互作用,还能与Tyr572和Tyr334形成疏水相互作用;FGPYF能够与活性位点氨基酸Arg483、Arg415、Asn382、Arg380、Tyr525和Tyr572形成氢键相互作用,与Arg483和Arg415形成离子键(盐桥),此外,还可以与Tyr525和Tyr572形成静电相互作用。这些相互作用能够促进抗氧化肽与Keap1蛋白之间形成稳定的复合物,并且根据蛋白与多肽的静电表面图也可发现多肽与蛋白契合较好。有研究表明,疏水氨基酸是Keap1-Nrf2复合物结合的主要贡献,特别是Keap1中Tyr334、Arg380、Arg415、Arg483、Asn382、Tyr525和Tyr572[52]。这与本研究中FGWGP、FGHPEW和FGPYF三条多肽与Keap1的分子对接结果一致。三条多肽均能与Keap1蛋白的关键氨基酸残基形成相互作用,尤其是疏水相互作用,从而可能影响Keap1-Nrf2复合物的稳定性,进一步调控Nrf2信号通路,发挥抗氧化作用。
本研究通过分析均方根偏差(RMSD)、均方根波动(RMSF)和回转半径(Rg)评估FGPYF、FGWGP和FGHPEW与Keap1结合的稳定性。RMSD是复合物相对于其初始位置原子坐标的均方根偏差,被视为评估系统稳定性的重要指标,较小的RMSD值表示系统更加稳定[53]。如图8(A)所示,在100 ns模拟过程中,FGPYF-Keap1和FGWGP-Keap1复合物的RMSD轨迹几乎相似,其RMSD值在0.1~0.16 nm之间波动,在0~10 ns的模拟时间内,其RMSD值总体上呈现上升趋势,随后变化趋势保持稳定,RMSD值稳定在0.13 nm左右。在0~20 ns,FGHPEW-Keap1复合物的RMSD值呈现快速上升趋势,在之后逐渐稳定,其RMSD值最终在1.5 nm左右波动,模拟结果表明,FGPYF-Keap1和FGWGP-Keap1复合物的RMSD值波动较小,结构稳定性更高。各复合物的RMSD涨落值均在合理范围内,表明模拟过程中体系中各复合物的结构是平衡的。Rg用于反映单个氨基酸残基的均方根距离,用于描述蛋白质整体结构的紧密度,Rg值越小表示复合物结构稳定性更好[54]。如图8(B)所示,在100 ns的模拟过程中,FGPYF-Keap1和FGWGP-Keap1和FGHPEW-Keap1复合物的Rg值分别稳定在1.71、1.72、2.16 nm左右。FGPYF-Keap1和FGWGP-Keap1复合物Rg值的总体趋势都是稳定的,而FGHPEW-Keap1发生了明显波动,表明FGPYF-Keap1和FGWGP-Keap1复合物的结构是紧凑且稳定的。RMSF值表示蛋白质与小分子复合物中单个氨基酸在模拟时间内的波动程度,用于衡量复合物不同区域的柔性,波动越大,意味着残基越灵活,蛋白质结构越不稳定[55]。如图8(C)所示,FGPYF-Keap1和FGWGP-Keap1复合物的RMSF轨迹波动趋势相似,其RMSF值均在0.05~0.25 nm之间。FGHPEW-Keap1复合物RMSF值则基本在0.2~0.4 nm之间,Keap1残基在380~394、429~439、490~501之间波动较大,这可能是因为这些位点上的残基参与了多肽与Keap1的相互作用。溶剂可及表面积(SASA)是反映分子或残基与溶剂接触面积的量化指标,SASA越小表明蛋白小分子结合越紧密[56]。由图8(D)可知,FGPYF-Keap1、FGWGP-Keap1和FGHPEW-Keap1的SASA值均较低,进一步表明了蛋白小分子形成了较为紧密的结合,这与虚拟筛选的结果一致。以上结果表明,FGWGP、FGPYF和FGHPEW均可以与Keap1紧密结合为稳定的构象。
本研究以白芸豆为原料,通过单因素结合响应面法确定菌-酶协同法制备WKBPs最佳工艺条件,得到了高得率及抗氧化活性的WKBPs。氨基酸组成成分及GPC结果显示WKBPs分子量主要集中在3 kDa以下,且具有潜在的抗氧化活性。超滤后组分WKBPs3表现出最好的抗氧化活性,其DPPH自由基清除率、ABTS+自由基清除率和羟自由基清除率的IC50分别为0.307、0.310和0.361 mg/mL,总抗氧化能力在1 mg/mL的浓度下可以达到0.66±0.0018 mmol Fe2+/g。通过LC-MS/MS质谱分析及虚拟筛选出3条潜在的抗氧化肽,分别为FGWGP、FGHPEW和FGPYF。分子对接结果表明,3条肽主要通过氢键、疏水相互作用和静电相互作用等与Keap1蛋白活性位点结合形成稳定的复合物,抑制Keap1与Nrf2的结合,从而调控Keap1-Nrf2通路发挥抗氧化作用。通过分子动力学模拟进一步验证FGWGP、FGHPEW和FGPYF可以与Keap1紧密结合形成稳定的构象。综上,FGWGP、FGHPEW和FGPYF可作为新型抗氧化肽被进一步开发和利用,本研究为白芸豆抗氧化肽产品的研发提供技术参考及理论基础,但当前的研究仅局限于WKBPs的提取、体外活性表征及抗氧化活性肽序列的筛选,未来可以基于细胞和动物实验进一步验证3条多肽在体内的生物学功能,为白芸豆作为功能性食品改善人体健康提供科学依据。

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2026年第47卷第3期
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doi: 10.13386/j.issn1002-0306.2024120200
  • 接收时间:2024-12-17
  • 首发时间:2026-10-25
  • 出版时间:2026-02-01
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  • 收稿日期:2024-12-17
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    1黑龙江八一农垦大学食品学院,黑龙江大庆 163319
    2国家杂粮工程技术中心,黑龙江大庆 163319
    3厦门海洋职业技术学院,福建厦门 361100
    4中国食品发酵工业研究院有限公司,功能主食创制与慢病营养干预北京市重点实验室,北京 100015
    5上海理工大学健康科学与工程学院,上海 200093
    6安徽省农业科学院皖北研究院,安徽阜阳 236600

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王颖(1979−),女,博士,教授,研究方向:农产品加工与贮藏工程及食品质量安全,E-mail:。
张璐(1987−),女,博士,高级工程师,研究方向:功能食品开发与精准营养及功效评价,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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