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Background Middle East respiratory syndrome coronavirus (MERS-CoV) continues to cause sporadic zoonotic infections with a case-fatality rate of approximately 35%, with recent 2025 surveillance confirming ongoing activity internationally. No specific antivirals or vaccines have been approved. Viral papain-like protease (PLpro) is essential for polyprotein processing making it a high-priority biochemical lead. Fisetin has been tested in clinical trials for its senolytic and anti-inflammatory activity and has demonstrated inhibitory activity against other coronavirus enzymes. However, it has not been evaluated as inhibitor for MERS-CoV PLpro. This study investigates fisetin as a novel MERS-CoV PLpro inhibitor. Methods Recombinant MERS-CoV PLpro was expressed in E. coli BL21 (DE3) and purified by Ni-NTA chromatography. Fisetin’s inhibitory potency was quantified by fluorogenic protease assay (Z-RLRGG-AMC substrate) and thermal shift assay (TSA). The binding interface was characterised by 100 ns all-atom MD simulations from both closed and open PLpro conformations, and independently cross-validated by AI co-folding using Boltz-2. Results Fisetin inhibited MERS-CoV PLpro with an IC 50 of 40.58 µM. TSA revealed concentration-dependent destabilisation (ΔTm −7.66 to −20.09 °C), a signature distinct from our previously characterised inhibitors. Contact frequency analysis localised stable fisetin engagement to a catalytic-domain pocket (residues 164–209; frequency 0.71–1.00) enclosed, while open conformation showed only diffuse surface sampling. Boltz-2 independently placed fisetin at the same pocket, with five of six predicted contacts overlapping the MD set (Jaccard 0.545; Spearman ρ = 0.43, p < 10 −15 ). Conclusion Fisetin is a dietary-derived MERS-CoV PLpro inhibitor engaging a catalytic-domain pocket distinct from the binding regions identified for our previously characterised inhibitors. Available human safety and pharmacokinetic data support further investigation of fisetin, particularly through cellular antiviral validation, formulation optimization, and combination studies.
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Alaofi et al. (2026) studied this question.
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