Identification and molecular mechanism of novel tyrosinase inhibitory peptides from collagen

酪氨酸酶 三肽 化学 生物化学 抑制性突触后电位 生物信息学 氨基酸 生物 神经科学 基因
作者
Wenjun Xue,Xuan Liu,Wenzhu Zhao,Zhipeng Yu
出处
期刊:Journal of Food Science [Wiley]
卷期号:87 (6): 2744-2756 被引量:16
标识
DOI:10.1111/1750-3841.16160
摘要

This study aimed to identify novel tyrosinase inhibitory peptides from collagen of donkey by combining in silico screening with in vitro activity verification, and to elucidate inhibition mechanism based on molecular docking and molecular dynamics simulation. Three tripeptides, that is, Asp-Gly-Leu (DGL), Gly-Ala-Arg (GAR), and Ser-Asp-Trp (SDW) were identified and exerted potent tyrosinase inhibitory activities, with IC50 values of 0.47 ± 0.01 mM, 1.13 ± 0.04 mM, and 2.08 ± 0.01 mM, respectively. Each of three identified peptides had hydrophobic amino acids and could stably and closely bind with the active pocket of tyrosinase. Hydrogen bonds played the most important roles in impacting the structure stabilities of the peptide-tyrosinase complexes. Moreover, His85, His244, His259, and Asn260 were the key residues to drive the interactions between the peptides and tyrosinase. Overall, collagen-derived peptides DGL, GAR, and SDW from donkey had great potential as tyrosinase inhibitory peptides. PRACTICAL APPLICATION: This study has suggested that three tripeptides DGL, GAR, and SDW derived from collagen of donkey have potent tyrosinase inhibitory activity. These novel collagen-derived peptides had great potential to be applied as tyrosinase inhibitory peptides to prevent and improve hyperpigmentation disorders and other tyrosinase-related problems in the food industry. And this work is expected to provide a theoretical basis for the development of novel, safe, and effective tyrosinase inhibitory peptides.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
卓天宇完成签到,获得积分10
1秒前
柚子完成签到 ,获得积分10
1秒前
550发布了新的文献求助10
1秒前
D1fficulty完成签到,获得积分10
1秒前
2秒前
2秒前
OmmeHabiba发布了新的文献求助10
3秒前
彪壮的如松完成签到,获得积分10
3秒前
5秒前
mango3005发布了新的文献求助10
6秒前
科研通AI5应助鳗鱼落雁采纳,获得10
8秒前
surfing完成签到,获得积分10
8秒前
ZYK完成签到,获得积分10
8秒前
冰渣凉发布了新的文献求助10
9秒前
OmmeHabiba完成签到,获得积分10
9秒前
9秒前
科研通AI5应助挑片岛屿采纳,获得10
10秒前
在水一方应助包容沛蓝采纳,获得10
11秒前
surfing发布了新的文献求助30
11秒前
火星上冥茗完成签到,获得积分10
11秒前
可靠的南露完成签到,获得积分10
13秒前
Song完成签到 ,获得积分10
13秒前
14秒前
14秒前
zzzzzzz发布了新的文献求助10
15秒前
15秒前
morry5007完成签到,获得积分10
17秒前
Akim应助冰渣凉采纳,获得10
17秒前
18秒前
19秒前
希望天下0贩的0应助ANG采纳,获得10
20秒前
Julie发布了新的文献求助10
20秒前
酷波er应助李悟尔采纳,获得50
21秒前
大秀子发布了新的文献求助10
22秒前
鳗鱼落雁发布了新的文献求助10
24秒前
碧蓝亦玉完成签到,获得积分10
25秒前
NexusExplorer应助煜钧采纳,获得10
25秒前
Owen应助斯文的傲珊采纳,获得10
25秒前
26秒前
zzzzzzz完成签到,获得积分10
26秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Deciphering Earth's History: the Practice of Stratigraphy 200
New Syntheses with Carbon Monoxide 200
Quanterion Automated Databook NPRD-2023 200
Interpretability and Explainability in AI Using Python 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3835028
求助须知:如何正确求助?哪些是违规求助? 3377507
关于积分的说明 10498840
捐赠科研通 3096984
什么是DOI,文献DOI怎么找? 1705397
邀请新用户注册赠送积分活动 820539
科研通“疑难数据库(出版商)”最低求助积分说明 772123