首页> 外文OA文献 >Rigorous Model-Based Design and Experimental Verification of Enzyme-Catalyzed Carboligation under Enzyme Inactivation
【2h】

Rigorous Model-Based Design and Experimental Verification of Enzyme-Catalyzed Carboligation under Enzyme Inactivation

机译:基于严格的基于模型的酶催化胶粘剂的设计与实验验证

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。
获取外文期刊封面目录资料

摘要

Enzyme catalyzed reactions are complex reactions due to the interplay of the enzyme, the reactants, and the operating conditions. To handle this complexity systematically and make use of a design space without technical restrictions, we apply the model based approach of elementary process functions (EPF) for selecting the best process design for enzyme catalysis problems. As a representative case study, we consider the carboligation of propanal and benzaldehyde catalyzed by benzaldehyde lyase from Pseudomonas fluorescens (PfBAL) to produce (R)-2-hydroxy-1-phenylbutan-1-one, because of the substrate dependent reaction rates and the challenging substrate dependent PfBAL inactivation. The apparatus independent EPF concept optimizes the material fluxes influencing the enzyme catalyzed reaction for the given process intensification scenarios. The final product concentration is improved by 13% with the optimized feeding rates, and the optimization results are verified experimentally. In general, the rigorous model driven approach could lead to selecting the best existing reactor, designing novel reactors for enzyme catalysis, and combining protein engineering and process systems engineering concepts.
机译:酶催化反应由于酶,反应物和操作条件的相互作用而是复杂的反应。为了系统地处理这种复杂性并利用无技术限制的设计空间,我们应用基于模型的基于基础过程功能(EPF)的方法,以选择酶催化问题的最佳过程设计。作为代表性的案例研究,我们考虑由苯甲醛裂解酶(PFBAL)催化的丙醛和苯甲醛的胶结化,因为基材依赖性反应速率和基质依赖性反应速率和苯甲醛(PFBAL)产生(R)-2-羟基-1-苯基丁丹-1-1具有挑战性的基质依赖性PFBAL灭活。该装置独立的EPF概念优化了影响给定过程强化情景的酶催化反应的材料助熔剂。最终产品浓度随优化的饲料速率提高13%,实验验证优化结果。通常,严谨的模型驱动方法可能导致选择最佳的现有反应器,为酶催化设计新型反应器,以及组合蛋白质工程和工艺系统工程概念。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号