Improving thermostability of a PL 5 family alginate lyase with combination of rational design strategies

热稳定性 氢键 突变体 化学 合理设计 基质(水族馆) 动力学 立体化学 生物化学 材料科学 有机化学 生物 纳米技术 分子 基因 物理 量子力学 生态学
作者
Licheng Zhou,Qing Cheng Meng,Ran Zhang,Bo Jiang,Qun Wu,Jingjing Chen,Tao Zhang
出处
期刊:International Journal of Biological Macromolecules [Elsevier]
卷期号:242 (Pt 2): 124871-124871 被引量:14
标识
DOI:10.1016/j.ijbiomac.2023.124871
摘要

Alginate lyases with strict substrate specificity possess potential in directed production of alginate oligosaccharides with specific composition. However, their poor thermostability hampered their applications in industry. In this study, an efficient comprehensive strategy including sequence-based analysis, structure-based analysis, and computer-aid ΔΔGfold value calculation was proposed. It was successfully performed on alginate lyase (PMD) with strict poly-β-D-mannuronic acid substrate specificity. Four single-point variants A74V, G75V, A240V, and D250G with increased Tm of 3.94 °C, 5.21 °C, 2.56 °C, and 4.80 °C, respectively, were selected out. After ordered combined mutations, a four-point mutant (M4) was finally generated which displayed remarkable increase on thermostability. The Tm of M4 increased from 42.25 °C to 51.59 °C and its half-life at 50 °C was about 58.9-fold of PMD. Meanwhile, there was no obvious loss of enzyme activity (more than 90% retained). Molecular dynamics simulation analysis insisted that the improvement of thermostability might be attribute to the rigidified region A which might be caused by the newly formed hydrogen bonds and salt bridges introduced by mutations, the lower distance of original hydrogen bonds, and the more compact overall structures.
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
1秒前
1秒前
1秒前
2秒前
2秒前
mookie发布了新的文献求助30
2秒前
2秒前
3秒前
3秒前
科研通AI2S应助洒水员采纳,获得10
3秒前
CodeCraft应助KScrazy采纳,获得10
4秒前
control完成签到,获得积分10
4秒前
Amber完成签到,获得积分10
4秒前
完美世界应助勤恳平卉采纳,获得10
4秒前
汉堡包应助江江江采纳,获得10
4秒前
自由妙竹发布了新的文献求助10
5秒前
共享精神应助ZD采纳,获得10
5秒前
科研大捞发布了新的文献求助10
5秒前
5秒前
qq发布了新的文献求助10
5秒前
5秒前
粗暴的元柏完成签到 ,获得积分10
6秒前
curtisness完成签到,获得积分0
7秒前
7秒前
英俊的铭应助dongdong采纳,获得10
7秒前
大模型应助tong采纳,获得10
7秒前
7秒前
7秒前
7秒前
自然归尘发布了新的文献求助10
7秒前
8秒前
cq完成签到,获得积分10
8秒前
CodeCraft应助随便采纳,获得10
8秒前
8秒前
耶耶发布了新的文献求助10
8秒前
xmq发布了新的文献求助10
9秒前
木槿发布了新的文献求助10
9秒前
故意的秋烟完成签到,获得积分10
10秒前
10秒前
量子星尘发布了新的文献求助10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5720067
求助须知:如何正确求助?哪些是违规求助? 5258729
关于积分的说明 15290203
捐赠科研通 4869657
什么是DOI,文献DOI怎么找? 2614906
邀请新用户注册赠送积分活动 1564885
关于科研通互助平台的介绍 1522079