Computational Modeling of ACE2 Inhibitors for Development of Drugs Against Coronaviruses

Joshi, R.; Bansal, S.; Malik, D.; Singla, R.; Mishra, A.; Prakash, A.; Medhi, B.

Despite the declaration of SARS-CoV-2 infection as a pandemic on March 11, 2020 by the World Health Organization, till date, no effective treatment has been approved to combat the severity of this pandemic. Few antiviral and antimalarial drugs have been used for symptomatic treatment of COVID-19 infection, but none of the treatment strategies has provided promising results against this infection. As the journey of a vaccine is also very long, there is a need to repurpose the already approved drugs against this pandemic. The urge of studying the structural association of human ACE2, an entry receptor of the virus in the human body with the SARS-CoV-2, may lead to the invention of a new promising prophylactic as well as curative treatment options for the COVID-19 pandemic. This chapter covers the importance of human ACE2 receptors in pathophysiology of COVID-19 infection. Finally, the results of various computational studies have been elaborated in this chapter. The role of different classes of already approved drugs which have shown promise against SARS-CoV-2 infection in in silico docking and computational modeling experiments is summarized for their future prospects in the treatment of COVID-19 infection. They were chosen on the basis of their free binding energies and relative ligand scoring scales. Molecular docking tools like molecule operating environment (MOE), Glide, AutoDock Vina, and Swiss dock were used in many in silico experiments. Some of the potential treatment modalities found in literature survey were ACE inhibitors, antibiotics, anti-inflammatory, antineoplastic, phosphodiesterase inhibitors, hydroxychloroquine and chloroquine, and so on, which have been proved to be efficacious treatment options for SARS-CoV-2 infection by computational modeling of human ACE2 receptors.