Improved thermostability of proteinase K and recognizing the synergistic effect of Rosetta and FoldX approaches.

IF 2.6 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Protein Engineering Design & Selection Pub Date : 2021-02-15 DOI:10.1093/protein/gzab024
Yang Zhao, Daixi Li, Xue Bai, Manjie Luo, Yan Feng, Yilei Zhao, Fuqiang Ma, Guang-Yu Yang
{"title":"Improved thermostability of proteinase K and recognizing the synergistic effect of Rosetta and FoldX approaches.","authors":"Yang Zhao,&nbsp;Daixi Li,&nbsp;Xue Bai,&nbsp;Manjie Luo,&nbsp;Yan Feng,&nbsp;Yilei Zhao,&nbsp;Fuqiang Ma,&nbsp;Guang-Yu Yang","doi":"10.1093/protein/gzab024","DOIUrl":null,"url":null,"abstract":"<p><p>Proteinase K (PRK) is a proteolytic enzyme that has been widely used in industrial applications. However, poor stability has severely limited the uses of PRK. In this work, we used two structure-guided rational design methods, Rosetta and FoldX, to modify PRK thermostability. Fifty-two single amino acid conversion mutants were constructed based on software predictions of residues that could affect protein stability. Experimental characterization revealed that 46% (21 mutants) exhibited enhanced thermostability. The top four variants, D260V, T4Y, S216Q, and S219Q, showed improved half-lives at 69°C by 12.4-, 2.6-, 2.3-, and 2.2-fold that of the parent enzyme, respectively. We also found that selecting mutations predicted by both methods could increase the predictive accuracy over that of either method alone, with 73% of the shared predicted mutations resulting in higher thermostability. In addition to providing promising new variants of PRK in industrial applications, our findings also show that combining these programs may synergistically improve their predictive accuracy.</p>","PeriodicalId":54543,"journal":{"name":"Protein Engineering Design & Selection","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2021-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Protein Engineering Design & Selection","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/protein/gzab024","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 4

Abstract

Proteinase K (PRK) is a proteolytic enzyme that has been widely used in industrial applications. However, poor stability has severely limited the uses of PRK. In this work, we used two structure-guided rational design methods, Rosetta and FoldX, to modify PRK thermostability. Fifty-two single amino acid conversion mutants were constructed based on software predictions of residues that could affect protein stability. Experimental characterization revealed that 46% (21 mutants) exhibited enhanced thermostability. The top four variants, D260V, T4Y, S216Q, and S219Q, showed improved half-lives at 69°C by 12.4-, 2.6-, 2.3-, and 2.2-fold that of the parent enzyme, respectively. We also found that selecting mutations predicted by both methods could increase the predictive accuracy over that of either method alone, with 73% of the shared predicted mutations resulting in higher thermostability. In addition to providing promising new variants of PRK in industrial applications, our findings also show that combining these programs may synergistically improve their predictive accuracy.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
改善蛋白酶K的热稳定性,并认识到Rosetta和FoldX方法的协同效应。
蛋白酶K (PRK)是一种广泛应用于工业的蛋白水解酶。然而,稳定性差严重限制了核dprk的使用。在这项工作中,我们使用了两种结构导向的合理设计方法,Rosetta和FoldX来修饰PRK的热稳定性。基于软件预测可能影响蛋白质稳定性的残基,构建了52个单氨基酸转化突变体。实验表征显示46%(21个突变体)表现出增强的热稳定性。D260V、T4Y、S216Q和S219Q在69°C时的半衰期分别比亲本酶提高了12.4倍、2.6倍、2.3倍和2.2倍。我们还发现,选择两种方法预测的突变比单独使用任何一种方法都能提高预测精度,73%的共享预测突变导致更高的热稳定性。除了在工业应用中提供有希望的PRK新变体外,我们的研究结果还表明,将这些程序结合起来可能会协同提高它们的预测准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Protein Engineering Design & Selection
Protein Engineering Design & Selection 生物-生化与分子生物学
CiteScore
3.30
自引率
4.20%
发文量
14
审稿时长
6-12 weeks
期刊介绍: Protein Engineering, Design and Selection (PEDS) publishes high-quality research papers and review articles relevant to the engineering, design and selection of proteins for use in biotechnology and therapy, and for understanding the fundamental link between protein sequence, structure, dynamics, function, and evolution.
期刊最新文献
TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks. Correction to: De novo design of a polycarbonate hydrolase. Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids. Design of functional intrinsically disordered proteins. The shortest path method (SPM) webserver for computational enzyme design.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1