Enzyme-Mediated Carbon Dioxide Fixation: Catalytic Mechanisms and Computational Insights

Abstract

Carbon conversion technologies that transform carbon dioxide (CO₂) into high-value chemicals are pivotal for achieving sustainability. Among these, enzyme-mediated CO₂ fixation has recently gained increasing attention as a more sustainable and environmentally friendly alternative to traditional chemical methods, which typically require harsh conditions and impose significant environmental costs. Recent advances in computer-aided techniques have greatly facilitated the mechanistic understanding of CO₂-fixing enzymes and accelerated the development of enzyme-catalyzed carboxylation strategies. This review highlights recent progress in enzyme-mediated CO₂ fixation by categorizing key enzymes into four classes based on their cofactor or metal ion requirements: cofactor-independent enzymes, metal-dependent enzymes, nicotinamide adenine dinucleotide phosphate (NAD(P)H)-dependent enzymes, and prenylated flavin mononucleotide (prFMN)-dependent enzymes. We outline the basic principles and applications of molecular dynamics (MD) simulations and quantum mechanical (QM) calculations, which serve as essential tools for investigating enzyme conformational dynamics and reaction mechanisms. Through representative case studies, we demonstrate how computational analyses uncover catalytic features that enhance CO₂ conversion efficiency. These insights underscore the critical role of computer-aided approaches in guiding the rational design and optimization of biocatalysts, thereby advancing the application of enzyme-based systems for CO₂ fixation.

Keywords

CO₂ fixation / Enzyme-catalyzed carboxylation / Catalytic mechanisms / Cofactor-dependent enzymes / Computational modeling

Statement of the Use of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this manuscript, the author used ChatGPT(OpenAI) in order to improve the writing quality. After using this tool, the author reviewed and edited the content as needed and takes full responsibility for the content of the published article.

Author Contributions

Conceptualization, K.W., J.Z. and Q.L.; Writing—Original Draft, K.W.; Writing—Review & Editing, J.Z. and Q.L.; Supervision, J.Z. and Q.L.; Project Administration, J.Z. and Q.L.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data supporting this study are included within the article.

Funding

This research was funded by the National Natural Science Foundation of China (32571468, 32201030, U24A20365 and 32271319), the Science and Technology Department of Jilin Province (20230402041GH), the Development and Reform Commission of Jilin Province (2023C015), the Fundamental Research Funds of the Central Universities, China (2024-JCXK-11), and the Innovation Program for Graduate Students of Jilin University (2025CX127).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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