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Extended Bloch–McConnell equations for mechanistic analysis of hyperpolarized (13)C magnetic resonance experiments on enzyme systems

We describe an approach to formulating the kinetic master equations of the time evolution of NMR signals in reacting (bio)chemical systems. Special focus is given to studies that employ signal enhancement (hyperpolarization) methods such as dissolution dynamic nuclear polarization (dDNP) and involvi...

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Detalles Bibliográficos
Autores principales: Eykyn, Thomas R., Elliott, Stuart J., Kuchel, Philip W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Copernicus GmbH 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539799/
https://www.ncbi.nlm.nih.gov/pubmed/37904769
http://dx.doi.org/10.5194/mr-2-421-2021
Descripción
Sumario:We describe an approach to formulating the kinetic master equations of the time evolution of NMR signals in reacting (bio)chemical systems. Special focus is given to studies that employ signal enhancement (hyperpolarization) methods such as dissolution dynamic nuclear polarization (dDNP) and involving nuclear spin-bearing solutes that undergo reactions mediated by enzymes and membrane transport proteins. We extend the work given in a recent presentation on this topic (Kuchel and Shishmarev, 2020) to now include enzymes with two or more substrates and various enzyme reaction mechanisms as classified by Cleland, with particular reference to non-first-order processes. Using this approach, we can address some pressing questions in the field from a theoretical standpoint. For example, why does binding of a hyperpolarized substrate to an enzyme not cause an appreciable loss of the signal from the substrate or product? Why does the concentration of an unlabelled pool of substrate, for example [Formula: see text] C lactate, cause an increase in the rate of exchange of the [Formula: see text] C-labelled pool? To what extent is the equilibrium position of the reaction perturbed during administration of the substrate? The formalism gives a full mechanistic understanding of the time courses derived and is of relevance to ongoing clinical trials using these techniques.