QSARINS Based Computational Identification of Sars-Cov-2 Main Protease Inhibitors

The novel coronavirus SARS-CoV-2 responsible for COVID-19, for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches. One of the most important COVID-19 protein targets is the 3C-like (main) protease for which the crystal structure is known. In this study, we used QSAR methodology to identify compounds with potential inhibition activity for 3C-like protease. First we collect a large dataset of compounds, with experimental report of inhibition against SARS-CoV main protease, to develop a model using QSARIN software, with appropriate parameters for its fitting. The model is extensively validated according to OECD standards, so that its robustness, stability, low correlation of descriptors and good predictive power are proven. This model is employed for the virtual screening of the Drug Bank database and several compounds were identified as potential 3C-like protease inhibitors.