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Mechanistic Model for Prediction of Formate Dehydrogenase Kinetics Under Industrially Relevant Conditions

机译:工业相关条件下甲酸脱氢酶动力学预测的机理模型

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摘要

Formate dehydrogenase (FDH) from Candida boidinii is an important biocatalyst for the regeneration of the cofactor NADH in industrial enzyme-catalyzed reductions. The mathematical model that is currently applied to predict progress curves during (semi-)batch reactions has been derived from initial rate studies. Here, it is demonstrated that such extrapolation from initial reaction rates to performance during a complete batch leads to considerable prediction errors. This observation can be attributed to an invalid simplification during the development of the literature model. A novel mechanistic model that describes the course and performance of FDH-catalyzed NADH regeneration under industrially relevant process conditions is introduced and evaluated. Based on progress curve instead of initial reaction rate measurements, it was discriminated from a comprehensive set of mechanistic model candidates. For the prediction of reaction courses on long time horizons (>1 h), decomposition of NADH has to be considered. The model accurately describes the. regeneration reaction under all conditions, even at high concentrations of the substrate formate and thus is clearly superior to the existing model. As a result, for the first time, course and performance of NADH regeneration in industrial enzyme-catalyzed reductions can be accurately predicted and used to optimize the cost efficiency of the respective processes.
机译:来自博伊假丝酵母的甲酸脱氢酶(FDH)是工业酶催化还原反应中辅因子NADH再生的重要生物催化剂。目前用于预测(半)间歇反应过程中进度曲线的数学模型已从初始速率研究中得出。在此,证明了从初始反应速率到整个批次期间的性能的这种外推导致相当大的预测误差。该观察结果可归因于文献模型开发过程中的无效简化。介绍和评估了一种新颖的力学模型,该模型描述了FDH催化的NADH在工业相关工艺条件下的再生过程和性能。根据进度曲线而不是初始反应速率测量值,将其与一组全面的机械模型候选物区分开。为了预测长时间(> 1小时)内的反应过程,必须考虑分解NADH。该模型准确地描述了。即使在高浓度的甲酸酯底物下,在所有条件下的再生反应,也明显优于现有模型。结果,首次可以准确预测工业酶催化还原反应中NADH再生的过程和性能,并将其用于优化各个过程的成本效率。

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