In-Silico Screening and Molecular Dynamics Simulation of Drug Bank Experimental Compounds against SARS-CoV-2

Abstract

For the last few years, the world has been going through a difficult time, and the reason behind this is severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), one of the significant members of the Coronaviridae family. The major research groups have shifted their focus towards finding a vaccine and drugs against SARS-CoV-2 to reduce the infection rate and save the life of human beings. Even the WHO has permitted using certain vaccines for an emergency attempt to cut the infection curve down. However, the virus has a great sense of mutation, and the vaccine’s effectiveness remains questionable. No natural medicine is available at the community level to cure the patients for now. In this study, we have screened the vast library of experimental drugs of Drug Bank with Schrodinger’s maestro by using three algorithms: high-throughput virtual screening (HTVS), standard precision, and extra precise docking followed by Molecular Mechanics/Generalized Born Surface Area (MMGBSA). We have identified 3-(7-diaminomethyl-naphthalen-2-YL)-propionic acid ethyl ester and Thymidine-5′-thiophosphate as potent inhibitors against the SARS-CoV-2, and both drugs performed impeccably and showed stability during the 100 ns molecular dynamics simulation. Both of the drugs are among the category of small molecules and have an acceptable range of ADME properties. They can be used after their validation in in-vitro and in-vivo conditions.

Keywords

• SARS-CoV-2
• RNA-dependent RNA polymerase
• replication-transcription complex
• molecular docking
• molecular dynamics simulation