Long-Term Biocatalyst Performance: Mechanistic Prediction and Continuous Non-Isothermal Testing

ChemSusChem. 2022 May 6;15(9):e202102701. doi: 10.1002/cssc.202102701. Epub 2022 Apr 20.

Abstract

The assessment of the operational stability of biocatalysts by conventional direct determination of the total turnover number (TTN), a useful indicator of lifetime biocatalyst productivity, via continuous isothermal experiments tends to be time-consuming, material-intensive, and prone to disturbances, especially in case of rather stable catalysts. In the present work, we present and validate two alternative methods for estimating the TTN of a biocatalyst for any desired operating temperature. The first method is a mechanistic approach, built upon mathematical derivation of enzyme deactivation models derived from first principles, in which TTN can be calculated from two straightforward isothermal biochemical batch measurements. The second method relies on a few non-isothermal, continuous-mode experiments in conjunction with mathematical modeling to determine the intrinsic deactivation parameters of the biocatalyst. We verify both methods on the test case of TEM-1 β-lactamase-catalyzed penicillin G (Pen G) hydrolysis. Both alternative methods provide estimates of TTN which are typically within a factor of two to five or less of the values measured directly via lengthy, costly, and error-prone conventional isothermal aging tests. Therefore, both the mechanistic approach and the non-isothermal continuous approach are extremely valuable tools to enable calculation of catalyst cost contribution in continuous processing and to eliminate underperforming candidates in search of the most stable biocatalyst.

Keywords: TEM-1 β-lactamase; lifetime productivity; non-isothermal kinetics; operational stability; total turnover number.

MeSH terms

  • Catalysis
  • Hydrolysis
  • Kinetics
  • Models, Theoretical*
  • Temperature