Towards Precision Biocatalysis – Leveraging Inline NMR for Autonomous Experimentation in Flow Reactors

IF 6.1 Q1 CHEMISTRY, MULTIDISCIPLINARY
Felix Ott, Dr. Gudrun Gygli, Dr. Kersten S. Rabe, Prof. Dr. Christof M. Niemeyer
{"title":"Towards Precision Biocatalysis – Leveraging Inline NMR for Autonomous Experimentation in Flow Reactors","authors":"Felix Ott,&nbsp;Dr. Gudrun Gygli,&nbsp;Dr. Kersten S. Rabe,&nbsp;Prof. Dr. Christof M. Niemeyer","doi":"10.1002/cmtd.202400049","DOIUrl":null,"url":null,"abstract":"<p>Reactor automation is a transformative force for chemical processes, but the potential of reaction monitoring for machine-assisted autonomous biocatalytic reaction optimization is still largely unexplored. To address this gap, we report on automated reactor optimization for biocatalytic flow-through microreactors. For this purpose, the inline NMR analysis of an enzymatically catalyzed stereoselective reduction of a prochiral diketone was combined with a self-developed open-source analysis and control software. The algorithm is continuously fed with spectra from a benchtop NMR instrument acquired from a reaction solution from a microreactor filled with biocatalytically active materials and adjusts the flow rate of the pumps to achieve predetermined target concentrations of the product. We show that through this automated coupling of data analysis and process parameterization, for example, maximum conversion efficiency can be achieved for a given bioreactor. This work illustrates the potential of inline NMR reaction monitoring for biocatalytic processes and provides a starting point for innovation to develop automated processes for precision biocatalysis through integrated data analysis.</p>","PeriodicalId":72562,"journal":{"name":"Chemistry methods : new approaches to solving problems in chemistry","volume":"4 12","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cmtd.202400049","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemistry methods : new approaches to solving problems in chemistry","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cmtd.202400049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Reactor automation is a transformative force for chemical processes, but the potential of reaction monitoring for machine-assisted autonomous biocatalytic reaction optimization is still largely unexplored. To address this gap, we report on automated reactor optimization for biocatalytic flow-through microreactors. For this purpose, the inline NMR analysis of an enzymatically catalyzed stereoselective reduction of a prochiral diketone was combined with a self-developed open-source analysis and control software. The algorithm is continuously fed with spectra from a benchtop NMR instrument acquired from a reaction solution from a microreactor filled with biocatalytically active materials and adjusts the flow rate of the pumps to achieve predetermined target concentrations of the product. We show that through this automated coupling of data analysis and process parameterization, for example, maximum conversion efficiency can be achieved for a given bioreactor. This work illustrates the potential of inline NMR reaction monitoring for biocatalytic processes and provides a starting point for innovation to develop automated processes for precision biocatalysis through integrated data analysis.

Abstract Image

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.30
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信