负载乳源抗菌肽BCp12的复合乳液制备工艺研究
Preparation of Composite Emulsion Loaded with Milk Derived Antimicrobial Peptide BCp12
袁子又 1赵琼 1赵兴文 2杨婷婷 1黄艾祥1
作者信息
- 1. 云南农业大学食品科学技术学院,昆明 650201
- 2. 大理农林职业技术学院食品工程系,大理 671003
- 折叠
摘要
本研究利用乳清分离蛋白(WPI)和羧甲基壳聚糖(CMCS)为载体,负载乳源抗菌肽BCp12;以复合乳液的抑菌率为指标,优化最佳制备工艺,利用扫描电镜(SEM)和分子对接技术进一步揭示复合乳液潜在的交联机制.结果表明,复合乳液的最佳制备工艺为:WPI∶CMCS= 1∶1.5、抗菌肽BCp12浓度为1 mg/mL;复合乳液对大肠杆菌和金黄色葡萄球菌的抑菌率分别为74.56±0.61%和70.58±0.44%,对大肠杆菌和金黄色葡萄球菌的抑菌直径分别为20.50±1.08 mm和19.33±0.85 mm.SEM显示复合乳液质地细腻且均一,三种物质具有良好的相容性.分子对接发现BCp12-WPI-CMCS的复合乳液主要通过C=O、-NH2及-OH形成氢键相互结合,其中BCp12中的Y1位氨基酸是最佳结合位点.本研究为BCp12-WPI-CMCS复合乳液的开发和保鲜应用提供一定的技术参考.
Abstract
In this study,whey protein isolate(WPI)and carboxymethyl chitosan(CMCs)were used as carriers to load the milk derived antimicrobial peptide BCp12,and the antimicrobial rate of the composite lotion was used as an index to optimize the optimal preparation process.The potential crosslinking mechanism of the composite lotion was further revealed by scanning electron microscope(SEM)and molecular docking.The results showed that the best preparation process of the composite lotion was WPI:CMCs 1:1.5,the concentration of bcp12 was 1 mg/mL,and the antimicrobial rates against Escherichia coli and Staphylococcus aureus were 74.56±0.61%and 70.58±0.44%,respectively;The bacteriostatic diameters of Escherichia coli and Staphylococcus aureus were 20.50±1.08 mm and 19.33±0.85 mm,respectively.It can be seen from the scanning electron microscope that the composite lotion has fine and uniform texture,and the three substances have good compatibility.Molecular docking showed that the BCp12-WPI-CMCs composite lotion was mainly bound by hydrogen bonds formed by C = O,-NH2 and-OH,and the Y1 amino acid in BCp12 may be the best binding site.This study provided technical references for the application and development of BCp12-WPI-CMCs composite lotion.
关键词
抗菌肽BCp12/羧甲基壳聚糖/乳清分离蛋白/扫描电镜/分子对接Key words
Antimicrobial peptide BCp12/Carboxymethyl chitosan/Whey protein isolate/Scanning electron microscope/Molecular docking引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据