The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains to be a serious threat due to the lack of a specific therapeutic agent. Computational methods are particularly suitable for rapidly fight against SARS-CoV-2. This present research aims to systematically explore the interaction mechanism of a series of novel bicycloproline-containing SARS-CoV-2 M
pro
inhibitors through integrated computational approaches. We designed six structurally modified novel SARS-CoV-2 M
pro
inhibitors based on the QSAR study. The four designed compounds with higher docking scores were further explored through molecular docking, molecular dynamics (MD) simulations, free energy calculations, and residual energy contributions estimated by the MM-PBSA approach, with comparison to compound 23(PDB entry 7D3I). This research not only provides robust QSAR models as valuable screening tools for the development of anti-COVID-19 drugs, but also proposes the newly designed SARS-CoV-2 M
pro
inhibitors with nanomolar activities that can be potentially used for further characterization to treat SARS-CoV-2 virus.
The normal expression of the main protease (Mpro) plays a vital role in the life cycle of the coronavirus. Highly active inhibitors could inhibit the normal circulation of the main...
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