Multiscale modeling of enzyme-catalyzed methanol production by particulate methane monooxygenase
Date of Award
Doctor of Philosophy (PhD)
Daniela S. Mainardi
In this work, the conversion of methane to methanol by the particulate Methane Monooxygenase (pMMO) enzyme is investigated using a multi-scale modeling approach. This enzyme participates in carbon cycling and aids in the removal of harmful atmospheric methane, converting it to methanol. The interaction between pMMO and a neighboring enzyme that is present in the same organism is studied, and the unknown pMMO active site is elucidated and tested for methane oxidation towards the production of methanol.
Fundamental knowledge of pMMO's mechanism is not fully understood. Understanding how this enzyme works in nature will provide information towards designing efficient synthetic catalysts through biomimetics, which can mitigate the harmful effects of methane in the atmosphere. These studies could also lead to the development of new synthetic catalysts that could impact the use of methanol as a cleaner, and greener, energy source. The practical application of this study would become fruitful once the mechanism is determined, mimicked, and then applied to create biofuels, synthetically.
This work focuses on the fundamental research of the kinetics of an important catalyzed chemical reaction that relates to environmental biocatalysis, and involves atmospheric methane consumption (oxidation) for the production of fuel (methanol). Mimicking these same reactions in industrial settings has the potential to also reduce the harmful effects of methane while producing methanol as a desirable alternative fuel.
Although experimental techniques have indicated a region of interest where the reaction is thought to take place, the novelty of this research begins with uniquely studying the interactions between MDH and pMMO by examining the docking regions of the enzymes to deduce an active region. Secondly, reaction mechanisms are proposed, and information about the kinetics of the methane oxidation process reaction is obtained. Transition state structures are determined and energy barriers estimated. Lastly, macroscopic reaction rates are determined through Kinetic Monte Carlo calculations to support the favored reaction pathways and demonstrate real-time oxidation reactions while observing the behavior of the pMMO system. Details from each of these techniques provide information to further the understanding of how pMMO oxidizes methane.
Bearden, Katherine K., "" (2013). Dissertation. 280.