藜麦血管紧张素转化酶抑制肽的分离纯化与鉴定

Isolation,Purification,and Characterization of Quinoa Angiotensin-Converting Enzyme Inhibitory Peptide

研究采用了一系列分离纯化技术,包括离子交换层析法、葡聚糖凝胶层析法以及反相高效液相色谱法(Reversed-phase high performance liquid chromatography,RP-HPLC),旨在从藜麦蛋白酶解物中分离并纯化出具有潜在活性的肽组分。评价过程中,以血管紧张素转化酶(Angiotensin converting enzyme,ACE)抑制率为主要指标,通过该标准来筛选出具备良好ACE抑制活性的肽段。为更精确地鉴定这些活性肽的序列,采用液相色谱-串联质谱(Liquid chromatogry-tandem mass spectrometry,LC-MS/MS)技术进行细化分离。采用分子对接进一步深入解析肽段与ACE之间的作用机制,构建肽段与ACE的结合模型。研究结果表明,离子交换层析分离得到3个组分中以G-2组分具有更好降压活性,其ACE抑制率达到(47.22±1.61)%。葡聚糖凝胶层析分离得到3个组分继续收集进行RP-HPLC分离纯化,收集4个组分中A1组分具有更好降压活性。再通过质谱分析,得到肽段共105条。通过对肽段大小长短、认知度以及C端氨基酸性质进行初步筛选,最后根据分子对接模型预测鉴定筛选出最佳结合肽段GRCPGGLCCSK。该研究旨在为藜麦功能性肽的开发利用提供理论参考。

A series of separation and purification techniques,including ion exchange chromatography,sephadex gel chromatography,and reverse phase high-performance liquid chromatography(RPHPLC),were employed to isolate and purify potentially active peptide components from quinoa protease hydrolysates.During the evaluation process,the inhibition rate of angiotensin-converting enzyme(ACE)was used as the primary criterion to screen for peptide segments with good ACE inhibitory activity.Liquid chromatography-tandem mass spectrometry(LC-MS/MS)was utilized for detailed separation to accurately identify the sequences of these active peptides.Molecular docking was performed to further analyze the mechanism of action between the peptide segments and ACE,constructing a binding model of the peptide and ACE.The results indicated that among the three components isolated by ion exchange chromatography,the G-2 component exhibited better antihypertensive activity,with an ACE inhibition rate reaching(47.22±1.61)%.Three components were further collected from dextran gel chromatography and subjected to separation and purification by RP-HPLC.Among the four components collected,the A1component showed superior antihypertensive activity.A total of 105 peptide segments were identified through mass spectrometry,followed by preliminary screening based on segment size,length,recognition degree and C-terminal amino acid properties.Ultimately,the best binding peptide GRCPGGLCCSK was selected using molecular docking modeling approach.The study aims to provide a theoretical reference for the development and utilization of functional peptides from quinoa.