In silico drug designing for COVID-19: an approach of high-throughput virtual screening, molecular, and essential dynamics simulations.

Severe acute respiratory syndrome-coronavirus2 (SARS-CoV2), a new coronavirus has emerged in Wuhan city of China, December 2019 causing pneumonia named Coronavirus disease-19 (COVID-19), which has spread to the entire world. By January 2021, number of confirmed cumulative cases crossed ∼104 million worldwide. Till date, no effective treatment or drug is available for this virus. Availability of X-ray structures of SARS-CoV2 main protease (Mpro) provides the potential opportunity for structure-based drug designing. Here, we have made an attempt to do computational drug design by targeting main protease of SARS-CoV2. High-throughput virtual screening of million molecules and natural compounds databases were performed followed by docking. After that, the protein-ligand complexes were optimized and rescoring of binding energies were accomplished through molecular dynamics simulation and Molecular mechanics Poisson Boltzmann surface area approaches, respectively. In addition, conformational effect of various ligands on protein was also examined through essential dynamics simulation. Three compounds namely ZINC14732869, ZINC19774413, and ZINC19774479 were finally filtered that displayed better binding affinities than N3 (known) inhibitor and formed conformationally stable complexes. Hence, the current study features the potential novel inhibitors against main protease of SARS-CoV2 which might provide an effective therapeutic strategy against COVID-19.Communicated by Ramaswamy H. Sarma.