Estimating the binding energetics of reversible covalent inhibitors of the SARS-CoV-2 main protease: an in silico study

The main protease (M-pro) of the SARS-CoV-2 virus is an attractive therapeutic target for developing antivirals to combat COVID-19. M-pro is essential for the replication cycle of the SARS-CoV-2 virus, so inhibiting M-pro blocks a vital piece of the cell replication machinery of the virus. A promising strategy to disrupt the viral replication cycle is to design inhibitors that bind to the active site cysteine (Cys145) of the M-pro. Cysteine targeted covalent inhibitors are gaining traction in drug discovery owing to the benefits of improved potency and extended drug-target engagement. An interesting aspect of these inhibitors is that they can be chemically tuned to form a covalent, but reversible bond, with their targets of interest. Several small-molecule cysteine-targeting covalent inhibitors of the M-pro have been discovered-some of which are currently undergoing evaluation in early phase human clinical trials. Understanding the binding energetics of these inhibitors could provide new insights to facilitate the design of potential drug candidates against COVID-19. Motivated by this, we employed rigorous absolute binding free energy calculations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations to estimate the energetics of binding of some promising reversible covalent inhibitors of the M-pro. We find that the inclusion of enhanced sampling techniques such as replica-exchange algorithm in binding free energy calculations can improve the convergence of predicted non-covalent binding free energy estimates of inhibitors binding to the M-pro target. In addition, our results indicate that binding free energy calculations coupled with multiscale simulations can be a useful approach to employ in ranking covalent inhibitors to their targets. This approach may be valuable in prioritizing and refining covalent inhibitor compounds for lead discovery efforts against COVID-19 and other coronavirus infections.