堇叶碎米荠低聚肽制备工艺优化及结构特征、氧化活性研究
Preparation,structural characteristics and antioxidant activity of Cardamine violifolia oligopeptides
问小龙 1向极钎 2张亮 1李亚杰 1龙澜3
作者信息
- 1. 恩施土家族苗族自治州农业科学院,湖北 恩施 445000
- 2. 恩施土家族苗族自治州农业科学院,湖北 恩施 445000;湖北省富硒产业技术研究院,湖北 恩施 445000
- 3. 湖北省富硒产业技术研究院,湖北 恩施 445000
- 折叠
摘要
目的:制备堇叶碎米荠低聚肽,并拓展其应用范围.方法:以堇叶碎米荠为原料,使用碱性蛋白酶酶解,采用超滤膜进行分离浓缩,冷冻干燥后获取堇叶碎米荠低聚肽粉末,并对该低聚肽的结构和抗氧化活性进行分析.结果:堇叶碎米荠蛋白水解的最佳工艺条件为酶解温度50 ℃、酶解pH 10、加酶量4％、底物质量分数2％,此条件下水解度为17.9％;堇叶碎米荠低聚肽的蛋白质和多肽含量分别为49.01％和42.87％;该低聚肽在200～220 nm有较强的吸收带,具有酰胺键的特征吸收峰,二级结构以β-转角为主,相对分子质量＜1 000的约占90％;当堇叶碎米荠低聚肽质量浓度为20 mg/mL时,其羟自由基、ABTS自由基、DPPH自由基清除率分别为84.54％,98.22％,60.33％.结论:试验优化的堇叶碎米荠低聚肽制备工艺合理可行,堇叶碎米荠低聚肽具有抗氧化活性.
Abstract
Objective:This study aimed to prepare oligopeptidess of Camelina violifolia and expand its application range.Methods:C.violifolia protein was hydrolyzed by alkaline protease,and then used ultrafiltration membrane for isolating and concentrating,and obtained oligopeptides by freeze-drying.The structure and antioxidant activity of C.violifolia oligopeptides were analyzed.Results:The optimum conditions for the hydrolysis of C.violifolia protein were as follows:hydrolysis temperature 50 ℃,pH 10,enzyme dosage 4％,substrate concentration 2％,and hydrolysis degree 17.9％.The C.violifolia oligopeptides contents of protein and polypeptide were 49.01％and 42.87％,respectively.The oligopeptides had a strong absorption band at 200～220 nm,amide bond-specific absorption peaks,β-angle was the main secondary structure,and a 90％relative molecular weight of less than 1 000 Da.When the oligopeptides concentration was 20 mg/mL,the scavenging rates of hydroxyl radical,ABTS radical and DPPH radical were 84.54％,98.22％and 60.33％respectively.Conclusion:The preparation process of the oligopeptides of C.violifolia is reasonable and feasible.The oligopeptides have good antioxidant capacity.
关键词
堇叶碎米荠/低聚肽/结构特征/抗氧化Key words
Cardamine violifolia/oligopeptides/structural characteristics/antioxidant activity引用本文复制引用
基金项目
恩施州农科院青年创新基金项目(2021-003)
武汉市对口帮扶恩施州项目(21001)
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据