Thermodynamic principle to enhance enzymatic activity using the substrate affinity
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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-08-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-40471-y |
| _version_ | 1797558701561741312 |
|---|---|
| author | Hideshi Ooka Yoko Chiba Ryuhei Nakamura |
| author_facet | Hideshi Ooka Yoko Chiba Ryuhei Nakamura |
| author_sort | Hideshi Ooka |
| collection | DOAJ |
| description | 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 ] . |
| first_indexed | 2024-03-10T17:34:47Z |
| format | Article |
| id | doaj.art-13150f8af17a4de0ac622e040a023f2f |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:34:47Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-13150f8af17a4de0ac622e040a023f2f2023-11-20T09:53:39ZengNature PortfolioNature Communications2041-17232023-08-011411910.1038/s41467-023-40471-yThermodynamic principle to enhance enzymatic activity using the substrate affinityHideshi Ooka0Yoko Chiba1Ryuhei Nakamura2Biofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 HirosawaBiofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 HirosawaBiofunctional Catalyst Research Team, Center for Sustainable Resource Science, 2-1 HirosawaAbstract 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 ] .https://doi.org/10.1038/s41467-023-40471-y |
| spellingShingle | Hideshi Ooka Yoko Chiba Ryuhei Nakamura Thermodynamic principle to enhance enzymatic activity using the substrate affinity Nature Communications |
| title | Thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| title_full | Thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| title_fullStr | Thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| title_full_unstemmed | Thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| title_short | Thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| title_sort | thermodynamic principle to enhance enzymatic activity using the substrate affinity |
| url | https://doi.org/10.1038/s41467-023-40471-y |
| work_keys_str_mv | AT hideshiooka thermodynamicprincipletoenhanceenzymaticactivityusingthesubstrateaffinity AT yokochiba thermodynamicprincipletoenhanceenzymaticactivityusingthesubstrateaffinity AT ryuheinakamura thermodynamicprincipletoenhanceenzymaticactivityusingthesubstrateaffinity |