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19 January 2026

Uncovering Major Structural and Functional Features of Methyl-Coenzyme M Reductase (MCR) from Methanobrevibacter ruminantium in Complex with Two Substrates

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1
Precision Animal Nutrition Division, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Republic of Korea
2
Animal Breeding & Genetics Division, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Republic of Korea
3
Department of Animal Resources Science, College of Agriculture and Life Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci.2026, 27(2), 995;https://doi.org/10.3390/ijms27020995 
(registering DOI)
This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in Macromolecules

Abstract

Structural insights into methyl-coenzyme M reductase from Methanobrevibacter ruminantium (M. ruminantium) has implications for methane mitigation strategies. Methanogenesis in ruminants is a major contributor to global greenhouse gas emissions, primarily driven by the rumen archaeon M. ruminantium. Central to this process is methyl-coenzyme M reductase (Mcr), an enzyme that catalyzes the final step of methane production. Despite its significance as a chemogenetic target for methane mitigation, the high-resolution structure of M. ruminantium Mcr has remained elusive. Here, we employed homology modeling and CDOCKER simulations within the CHARMM force field to elucidate the structural and functional features of the M. ruminantium Mcr/ligand complexes. We characterized two distinct states: the reduced Mcroxi-silent state bound to HS-CoM and CoB-SH, and the oxidized Mcrsilent state bound to the heterodisulfide CoM-S-S-CoB. Alanine-scanning mutagenesis identified 71 and 62 key residues per active site for each state, respectively, revealing the fundamental determinants of structural stability and substrate selectivity on the Ni-F430 cofactor. Furthermore, structure-based pharmacophore modeling defined essential features (AAADDNNN and AAADDNN) that drive ligand binding. These findings provide a high-resolution molecular framework for the rational design of specific Mcr inhibitors, offering a robust starting point for developing broad-spectrum strategies to suppress enteric methane emissions.

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