Herein, we have generated ssRNA aptamers to inhibit SARS-CoV-2 Mpro, a protease necessary for the SARS-CoV-2 coronavirus replication. Because there is no aptamer 3D structure currently available in the databanks for this protein, first, we modeled an ssRNA aptamer using an entropic fragment-based strategy. We refined the initial sequence and 3D structure by using two sequential approaches, consisting of an elitist genetic algorithm and an RNA inverse process. We identified three specific aptamers against SARS-CoV-2 Mpro, called MAptapro, MAptapro-IR1, and MAptapro-IR2, with similar 3D conformations and that fall in the dimerization region of the SARS-CoV-2 Mpro necessary for the enzymatic activity. Through the molecular dynamic simulation and binding free energy calculation, the interaction between the MAptapro-IR1 aptamer and the SARS-CoV-2 Mpro enzyme resulted in the strongest and the highest stable complex; therefore, the ssRNA MAptapro-IR1 aptamer was selected as the best potential candidate for the inhibition of SARS-CoV-2 Mpro and a perspective therapeutic drug for the COVID-19 disease.
Keywords: COVID-19; aptamer-protein free energy calculation; aptamer-protein interaction; aptamers virtual screening; prediction of 3D RNA aptamer structure; single strand RNA aptamer.