Structural and Metabolic Characterization of Ni(I)-inhibitors Provide a Robust Anti-Methanogenicity Scoring System

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Abstract
Atmospheric methane (CH4) acts as a key contributor to global warming and a short-lived climate forcer. CH4 mitigation represents the most promising means to address short-term climate change. Ruminant enteric CH4 produced by methanogenic archaea represents 27.2% of global CH4 emissions. Only a few of the direct methanogenesis inhibitors identified bear high mitigation potential hence it is important to investigate their underlying modes of action. Here, we elucidated biophysical and thermodynamic interplay between known inhibitors and cofactor F430, to determine their stoichiometric ratios and binding affinities. We leverage this prior in a robust contrastive learning approach to functionally cluster known sixteen inhibitors and 53,959 bovine-linked metabolites. We demonstrate a multi-factor optimization protocol to identify putative inhibitors with: (i) high bacterial membrane permeability, (ii) no adverse effect to ruminal fermentation, (iii) known degradation pathway, and (iv) direct commercial availability. Subsequent in vitro assays and community metabolic modeling with a first set of eight treatment molecules revealed structo-metabolic priors that tie thermodynamic signatures of inhibition to metabolic flux shifts. We established a multi-scale workflow that transforms ostensibly negative compounds into mechanistic insight, linking rumen metabolic flux shifts to MCR–F430-Ni(I) inhibition chemistry as a foundation for rational methane-mitigation design. COVER

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