Enhanced targeting efficacy of baicalein analogues on the dimeric state of SARS-CoV-2 3CL protease compared to monomeric state

The COVID-19 pandemic caused by the novel coronavirus, SARS-CoV-2, has been a global threat affecting the entire world. It is a single-stranded RNA virus that belongs to the coronavirus family. In SARS-CoV2, the 3CL protease protein significantly contributes to viral replication and is responsible for viral polyprotein cleavage. These factors make 3CL protease a promising drug target to inhibit the growth of SARS-CoV-2. In this study, using in silico approaches, we have targeted the 3CL protease of SARS-CoV-2 to identify promising antiviral candidates for COVID-19 treatment. Here, 463 structural analogs of Baicalein compounds were collected initially, and by employing the quantitative structure-activity relationship (QSAR) technique on 76 antiviral compounds, screening was done against monomeric and dimeric versions of the target protein. Further, based on the molecular interaction studies and MD simulation, followed by validation of the obtained simulation trajectories using PCA and MM/PBSA calculation, it was observed that ligands showed better binding stability with dimeric proteins than monomeric proteins and can be used as suitable therapeutic candidates for SARS-CoV2 treatment. The MD simulation showed a favorable, robust outcome for the 46885476 when bound to the dimeric state. It matched the control in the number of hydrogen bonds and conformational stability. This molecule also directly impacted the catalytic dyads of the protein, suggesting potential inhibitory action. In addition, this study helps to accelerate the drug development process against SARS-CoV2 through the observed in-silico results, which need to be validated using clinical experiments in future studies.