Computational studies on phylogeny and drug designing using molecular simulations for COVID-19.

Nabi, Faisal; Ahmad, Owais; Khan, Yawar Ali; Nabi, Anas; Md Amiruddin, Hashmi; Abul Qais, Faizan; Masroor, Aiman; Hisamuddin, Malik; Uversky, Vladimir N; Khan, Rizwan Hasan

Since the first appearance of a novel coronavirus pneumonia (NCP) caused by a novel human coronavirus, and especially after the infection started its rapid spread over the world causing the COVID-19 (coronavirus disease 2019) pandemics, a very substantial part of the scientific community is engaged in the intensive research dedicated to finding of the potential therapeutics to cure this disease. As repurposing of existing drugs represents the only instant solution for those infected with the virus, we have been working on utilization of the structure-based virtual screening method to find some potential medications. In this study, we screened a library of 646 FDA approved drugs against the receptor-binding domain of the SARS-CoV-2 spike (S) protein and the main protease of this virus. Scoring functions revealed that some of the anticancer drugs (such as Pazopanib, Irinotecan, and Imatinib), antipsychotic drug (Risperidone), and antiviral drug (Raltegravir) have a potential to interact with both targets with high efficiency. Further we performed molecular dynamics simulations to understand the evolution in protein upon interaction with drug. Also, we have performed a phylogenetic analysis of 43 different coronavirus strains infecting 12 different mammalian species.Communicated by Ramaswamy H. Sarma.