Abstract

Understanding how to tune enzymatic activity is important not only for biotechnological applications, but also to elucidate the basic principles guiding the design and optimization of biological systems in nature. So far, the Michaelis-Menten equation has provided a fundamental framework of enzymatic activity. However, there is still no concrete guideline on how the parameters should be optimized towards higher activity. Here, we demonstrate that tuning the Michaelis-Menten constant (Km) to the substrate concentration ([S]) enhances enzymatic activity. This guideline (Km=[S]) was obtained mathematically by assuming that thermodynamically favorable reactions have higher rate constants, and that the total driving force is fixed. Due to the generality of these thermodynamic considerations, we propose Km=[S] as a general concept to enhance enzymatic activity. Our bioinformatic analysis reveals that the Km and in vivo substrate concentrations are consistent across a dataset of approximately 1000 enzymes, suggesting that even natural selection follows the principle Km=[S].

Currently, there is no well-defined strategy to increase the activity of enzymes. Here, the authors provide mathematical evidence that adjusting the Michaelis-Menten constant to the substrate concentration maximizes enzymatic activity.

Details

Title
Thermodynamic principle to enhance enzymatic activity using the substrate affinity
Author
Ooka, Hideshi 1   VIAFID ORCID Logo  ; Chiba, Yoko 2   VIAFID ORCID Logo  ; Nakamura, Ryuhei 3   VIAFID ORCID Logo 

 Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Japan (GRID:grid.509461.f) (ISNI:0000 0004 1757 8255) 
 Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Japan (GRID:grid.509461.f) (ISNI:0000 0004 1757 8255); Faculty of Life and Environmental Science, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Japan (GRID:grid.20515.33) (ISNI:0000 0001 2369 4728) 
 Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Japan (GRID:grid.509461.f) (ISNI:0000 0004 1757 8255); Earth-Life Science Institute (ELSI), Tokyo Institute of Technology, 2-12-IE-1 Ookayama, Meguro-ku, Japan (GRID:grid.32197.3e) (ISNI:0000 0001 2179 2105) 
Pages
4860
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2856660109
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.