Effect of Oriented Electric Fields on Biologically Relevant Iron–Sulfur Clusters: Tuning Redox Reactivity for Catalysis

Gaughan, Samuel J. H.; Hirst, Jonathan D.; Croft, Anna K.; Jäger, Christof M.

Abstract

Enzyme-based iron-sulfur clusters, exemplified in families such as hydrogenases, nitrogenases, and radical S-Adenosylmethionine enzymes, feature in many essential biological processes. The functionality of biological iron-sulfur clusters extends beyond simple electron transfer, relying primarily on the redox activity of the clusters, with a remarkable diversity for different enzymes. The active-site structure and the electrostatic environment in which the cluster resides direct this redox reactivity. Oriented electric fields in enzymatic active sites can be significantly strong, and understanding the extent of their effect on iron-sulfur cluster reactivity can inform first steps toward rationally engineering their reactivity. An extensive systematic density functional theory-based screening approach using OPBE/TZP has afforded a simple electric field-effect representation. The results demonstrate that the orientation of an external electric field of strength 28.8 MV cm-1 at the center of the cluster can have a significant effect on its relative stability in the order of 35 kJ mol-1. This shows clear implications for the reactivity of iron-sulfur clusters in enzymes. The results also demonstrate that the orientation of the electric field can alter the most stable broken-symmetry state, which further has implications on the directionality of initiated electron-Transfer reactions. These insights open the path for manipulating the enzymatic redox reactivity of iron-sulfur cluster-containing enzymes by rationally engineering oriented electric fields within the enzymes.

Citation

Gaughan, S. J. H., Hirst, J. D., Croft, A. K., & Jäger, C. M. (2022). Effect of Oriented Electric Fields on Biologically Relevant Iron–Sulfur Clusters: Tuning Redox Reactivity for Catalysis. Journal of Chemical Information and Modeling, 62(3), 591-601. https://doi.org/10.1021/acs.jcim.1c00791

• Journal Article Type: Article
• Acceptance Date: Dec 9, 2021
• Online Publication Date: Jan 19, 2022
• Publication Date: Feb 14, 2022
• Deposit Date: Dec 20, 2021
• Publicly Available Date: Jan 19, 2022
• Journal: Journal of Chemical Information and Modeling
• Print ISSN: 1549-9596
• Electronic ISSN: 1549-960X
• Publisher: American Chemical Society (ACS)
• Peer Reviewed: Peer Reviewed
• Volume: 62
• Issue: 3
• Pages: 591-601
• DOI: https://doi.org/10.1021/acs.jcim.1c00791
• Keywords: General Chemical Engineering; General Chemistry
• Public URL: https://nottingham-repository.worktribe.com/output/7052114
• Publisher URL: https://pubs.acs.org/doi/10.1021/acs.jcim.1c00791