AI and the World's Hard Problems · Life sciences · Nature (computational biology) · 2026-10-21
Discovery of potent inhibitors of rumen methane metabolism via an AI-assisted workflow
Ruminant methane emissions matter for both climate and sustainable livestock production, and this study built an AI-assisted workflow to discover inhibitors of MCR, the key enzyme of the terminal step of rumen methanogenesis. Ultra-fast virtual screening of about 23 million molecules yielded 26 candidates, of which 4 significantly inhibited methane production; structure-guided optimization led to the inhibitor PZON with an IC50 of 0.24 μM. PZON suppressed methane emissions by 73–98% across rumen microbiomes from four ruminant sources with no detectable cytotoxicity at concentrations exceeding 400-fold its IC50, and metatranscriptomic analyses confirmed reduced transcriptional activity of diverse methanogenic lineages and MCR.