QM/MM-Based Computational Studies Elucidating Molecular Mechanisms of Drug Design in the COVID-19 Treatment

We propose to apply the advanced molecular modeling approaches based on the quantum mechanics/molecular mechanics (QM/MM) and related molecular dynamics (QM/MM MD) methods to elucidate molecular mechanisms of inhibition of the SARS-CoV-2 Main protease by promising drugs. A cysteine protease designated in the current literature as the Main protease is a critical component of the Wuhan coronavirus (SARS-CoV-2). This enzyme is essential for viral replication and thus it is a potential drug target for the COVID-19 treatment. Since to date there are no clinically used inhibitors of the Main protease, considerable efforts are being commenced to test various chemicals to block the enzyme. The list of promising inhibitors is growing every day, but their experimental testing is labor- and resource-intensive, and require tremendous expenses. Here computational modeling can help, by assisting in the characterization of molecular mechanisms of interaction of prospective drug candidates with the Main protease. The proposed project focuses on the Main protease inhibition due to covalent binding of a drug molecule to the cysteine residue from the catalytic triad of the enzyme active site. When the critical amino acid residue Ser145 is bound by a drug molecule, the enzyme is poisoned and the virus cannot function. The proposed computational studies will provide quantitative information about reaction mechanisms of the known drugs and suggest routes for improving their effectiveness by structural modifications.