Computational methods for the study of carboxylases: The case of crotonyl-CoA carboxylase/reductase

Recabarren; R.; Gómez; A.G.; Vöhringer-Martinez; E.

Keywords: Carboxylase; CO2 binding; CO2 fixation; Molecular dynamics simulations; QM/MM

Abstract

The rising levels of atmospheric CO2 and its impact on climate change call for new methods to transform this greenhouse gas into beneficial compounds. Carboxylases have a significant role in the carbon cycle, converting gigatons of CO2 into biomass annually. One of the most effective and fastest carboxylases is crotonyl-CoA carboxylase/reductase (Ccr). To understand its underlying mechanism, we have developed computational methods and protocols based on all-atom molecular dynamics simulations. These methods provide the CO2 binding locations and free energy inside the active site, dependent on different conformations adopted by Ccr and the presence of the crotonyl-CoA substrate. Furthermore, the adaptive string method and quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations outline the CO2 fixation reaction via two different mechanisms. The direct mechanism involves a hydride transfer creating a reactive enolate, which then binds the electrophilic CO2 molecule, resulting in the carboxylated product. Alternatively, another mechanism involves the formation of a covalent adduct. Our simulations suggest that this adduct serves to store the enolate in a much more stable intermediate avoiding its reduction side reaction, explaining the enzyme's efficiency. Overall, this work presents computational methods for studying carboxylation reactions using Ccr as a model, providing general principles that can be applied to modeling other carboxylases. © 2024

Más información

Título según SCOPUS: Computational methods for the study of carboxylases: The case of crotonyl-CoA carboxylase/reductase
Título de la Revista: Methods in Enzymology
Volumen: 708
Editorial: ACADEMIC PRESS INC
Fecha de publicación: 2024
Página de inicio: 353
Página final: 387
Idioma: English
DOI:

10.1016/bs.mie.2024.10.025

Notas: SCOPUS