Biological carbon fixation benefits evaluation model construction and application based on atomic economy concept DOI Creative Commons
Dan Wang,

Mengdie Wang,

Zhiyao Peng

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 3, 2025

Abstract Current methods for evaluating biocarbon fixation efficiency (BCF), such as genome-scale metabolic models and life cycle assessment, lack consideration of reaction atom economy fail to connect genetic relationships with the process. To address these limitations, we introduced an atomic evaluation index centered on enzyme kinetics, named Economic Indicators Real Biological Carbon Fixation Atoms (EIRCBFA), proposed a machine learning-based model assess BCF at both conditions protein levels. Using gradient boosting, achieved R2 values 0.853 0.937, respectively, in five-fold cross-validation. The was validated by optimizing dihydroxyacetone (DHA) biosynthesis, where predictions were consistent traditional carbon trends. Notably, highest EIRCBFA mutant, FLS_F484E, produced 33.19 mg/L DHA, yield three times that wild-type enzyme. RAEKP provides valuable tool pathways their true fixed economy.

Язык: Английский

Biological carbon fixation benefits evaluation model construction and application based on atomic economy concept DOI Creative Commons
Dan Wang,

Mengdie Wang,

Zhiyao Peng

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 3, 2025

Abstract Current methods for evaluating biocarbon fixation efficiency (BCF), such as genome-scale metabolic models and life cycle assessment, lack consideration of reaction atom economy fail to connect genetic relationships with the process. To address these limitations, we introduced an atomic evaluation index centered on enzyme kinetics, named Economic Indicators Real Biological Carbon Fixation Atoms (EIRCBFA), proposed a machine learning-based model assess BCF at both conditions protein levels. Using gradient boosting, achieved R2 values 0.853 0.937, respectively, in five-fold cross-validation. The was validated by optimizing dihydroxyacetone (DHA) biosynthesis, where predictions were consistent traditional carbon trends. Notably, highest EIRCBFA mutant, FLS_F484E, produced 33.19 mg/L DHA, yield three times that wild-type enzyme. RAEKP provides valuable tool pathways their true fixed economy.

Язык: Английский

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