Thermodynamic principle to enhance enzymatic activity using the substrate affinity

Hideshi Ooka (), Yoko Chiba and Ryuhei Nakamura
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Hideshi Ooka: Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa
Yoko Chiba: Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa
Ryuhei Nakamura: Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 Hirosawa

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: 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 ( $${K}_{m}$$ K m ) to the substrate concentration ( $$[{{{{{\rm{S}}}}}}]$$ [ S ] ) enhances enzymatic activity. This guideline ( $${K}_{m}=[{{{{{\rm{S}}}}}}]$$ K m = [ 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 $${K}_{m}=[{{{{{\rm{S}}}}}}]$$ K m = [ S ] as a general concept to enhance enzymatic activity. Our bioinformatic analysis reveals that the $${K}_{m}$$ K m and in vivo substrate concentrations are consistent across a dataset of approximately 1000 enzymes, suggesting that even natural selection follows the principle $${K}_{m}=[{{{{{\rm{S}}}}}}]$$ K m = [ S ] .

Date: 2023
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DOI: 10.1038/s41467-023-40471-y

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