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A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase

Pyridoxal-5′-phosphate (PLP) is a cofactor in the reactions of over 160 enzymes, several of which are implicated in diseases. Methionine γ-lyase (MGL) is of interest as a therapeutic protein for cancer treatment. It binds PLP covalently through a Schiff base linkage and digests methionine, whose dep...

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Autores principales: Chen, Xingyu, Briozzo, Pierre, Machover, David, Simonson, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087591/
https://www.ncbi.nlm.nih.gov/pubmed/35558556
http://dx.doi.org/10.3389/fmolb.2022.886358
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author Chen, Xingyu
Briozzo, Pierre
Machover, David
Simonson, Thomas
author_facet Chen, Xingyu
Briozzo, Pierre
Machover, David
Simonson, Thomas
author_sort Chen, Xingyu
collection PubMed
description Pyridoxal-5′-phosphate (PLP) is a cofactor in the reactions of over 160 enzymes, several of which are implicated in diseases. Methionine γ-lyase (MGL) is of interest as a therapeutic protein for cancer treatment. It binds PLP covalently through a Schiff base linkage and digests methionine, whose depletion is damaging for cancer cells but not normal cells. To improve MGL activity, it is important to understand and engineer its PLP binding. We develop a simulation model for MGL, starting with force field parameters for PLP in four main states: two phosphate protonation states and two tautomeric states, keto or enol for the Schiff base moiety. We used the force field to simulate MGL complexes with each form, and showed that those with a fully-deprotonated PLP phosphate, especially keto, led to the best agreement with MGL structures in the PDB. We then confirmed this result through alchemical free energy simulations that compared the keto and enol forms, confirming a moderate keto preference, and the fully-deprotonated and singly-protonated phosphate forms. Extensive simulations were needed to adequately sample conformational space, and care was needed to extrapolate the protonation free energy to the thermodynamic limit of a macroscopic, dilute protein solution. The computed phosphate pK( a ) was 5.7, confirming that the deprotonated, −2 form is predominant. The PLP force field and the simulation methods can be applied to all PLP enzymes and used, as here, to reveal fine details of structure and dynamics in the active site.
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spelling pubmed-90875912022-05-11 A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase Chen, Xingyu Briozzo, Pierre Machover, David Simonson, Thomas Front Mol Biosci Molecular Biosciences Pyridoxal-5′-phosphate (PLP) is a cofactor in the reactions of over 160 enzymes, several of which are implicated in diseases. Methionine γ-lyase (MGL) is of interest as a therapeutic protein for cancer treatment. It binds PLP covalently through a Schiff base linkage and digests methionine, whose depletion is damaging for cancer cells but not normal cells. To improve MGL activity, it is important to understand and engineer its PLP binding. We develop a simulation model for MGL, starting with force field parameters for PLP in four main states: two phosphate protonation states and two tautomeric states, keto or enol for the Schiff base moiety. We used the force field to simulate MGL complexes with each form, and showed that those with a fully-deprotonated PLP phosphate, especially keto, led to the best agreement with MGL structures in the PDB. We then confirmed this result through alchemical free energy simulations that compared the keto and enol forms, confirming a moderate keto preference, and the fully-deprotonated and singly-protonated phosphate forms. Extensive simulations were needed to adequately sample conformational space, and care was needed to extrapolate the protonation free energy to the thermodynamic limit of a macroscopic, dilute protein solution. The computed phosphate pK( a ) was 5.7, confirming that the deprotonated, −2 form is predominant. The PLP force field and the simulation methods can be applied to all PLP enzymes and used, as here, to reveal fine details of structure and dynamics in the active site. Frontiers Media S.A. 2022-04-26 /pmc/articles/PMC9087591/ /pubmed/35558556 http://dx.doi.org/10.3389/fmolb.2022.886358 Text en Copyright © 2022 Chen, Briozzo, Machover and Simonson. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Chen, Xingyu
Briozzo, Pierre
Machover, David
Simonson, Thomas
A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title_full A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title_fullStr A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title_full_unstemmed A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title_short A Computational Model for the PLP-Dependent Enzyme Methionine γ-Lyase
title_sort computational model for the plp-dependent enzyme methionine γ-lyase
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087591/
https://www.ncbi.nlm.nih.gov/pubmed/35558556
http://dx.doi.org/10.3389/fmolb.2022.886358
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