Molecular mechanism of inhibition of COVID-19 main protease by β-adrenoceptor agonists and adenosine deaminase inhibitors using in silico methods

Novel coronavirus (COVID-19) responsible for viral pneumonia which emerged in late 2019 has badly affected the world. No clinically proven drugs are available yet as the targeted therapeutic agents for the treatment of this disease. The viral main protease which helps in replication and transcription inside the host can be an effective drug target. In the present study, we aimed to discover the potential of beta-adrenoceptor agonists and adenosine deaminase inhibitors which are used in asthma and cancer/inflammatory disorders, respectively, as repurposing drugs against protease inhibitor by ligand-based and structure-based virtual screening using COVID-19 protease-N3 complex. The AARRR pharmacophore model was used to screen a set of 22,621 molecules to obtain hits, which were subjected to high-throughput virtual screening. Extra precision docking identified four top-scored molecules such as +/--fenoterol, FR236913 and FR230513 with lower binding energy from both categories. Docking identified three major hydrogen bonds with Gly143, Glu166 and Gln189 residues. 100 ns MD simulation was performed for four top-scored molecules to analyze the stability, molecular mechanism and energy requirements. MM/PBSA energy calculation suggested that van der Waals and electrostatic energy components are the main reasons for the stability of complexes. Water-mediated hydrogen bonds between protein-ligand and flexibility of the ligand are found to be responsible for providing extra stability to the complexes. The insights gained from this combinatorial approach can be used to design more potent and bio-available protease inhibitors against novel coronavirus. Communicated by Ramaswamy H. Sarma

Automated summary

This study investigates the potential of drugs used for asthma and cancer/inflammatory disorders as repurposing drugs against the novel coronavirus protease. Through virtual screening and molecular dynamics simulation, four top-scored molecules were identified with lower binding energy. The findings provide insights for designing more potent protease inhibitors against the novel coronavirus.