The main protease (MPro) plays a crucial role in the Coronavirus life cycle and is a target for newly developed antivirals against SARS-CoV-2.... Show moreThe main protease (MPro) plays a crucial role in the Coronavirus life cycle and is a target for newly developed antivirals against SARS-CoV-2. MPro is conserved across various members of the coronavirus family. The enzyme of SARS-CoV-2 and other members of the coronavirus family share similar structures and functions, commonly existing as obligate dimers. However, MPro from MERS-CoV exhibits weaker dimerization and often exists as a monomer under biochemical assay conditions, which may not accurately reflect the conditions relevant to antiviral therapy in infected cells.Interestingly, because ligand binding increases dimerization, the addition of ligands has been reported to enhance MPro activity at low concentrations before reducing it at higher concentrations. This phenomenon, known as ligand-induced dimerization, was observed not only in biochemical assays of MERS-CoV MPro but also of SARS-CoV-2 mutated MPro with weakened dimerization. Unfortunately, there are currently no published biochemical models that quantitatively fit these non-monotonic concentration-response curves. This poses a significant challenge in estimating IC50 from these curves, which is an important metric for drug potency and commonly used in drug screening. As a result, predicting compound behavior in cellular models becomes challenging.To address this challenge, we developed an enzyme kinetic model that integrates dimerization and ligand binding. We utilized Bayesian regression for the model to fit datasets published in the aforementioned study of SARS-CoV-2 MPro. Subsequently, we adjusted the model to achieve a global fit for multiple datasets of MERS-CoV MPro and estimate IC50 values. Finally, we examined the correlation between estimated IC50 and cellular EC50, demonstrating that our model is capable of predicting cellular EC50 for the biphasic curves observed in MERS-CoV MPro. Show less
