Using integrated computational approaches to identify safe and rapid treatment for SARS-CoV-2

Abstract

SARS-CoV-2 is a new generation of coronavirus, which was first determined in Wuhan, China, in December 2019. So far, however, there no effective treatment has been found to stop this new generation of coronavirus but discovering of the crystal structure of SARS-CoV-2 main protease (SARS-CoV-2 Mpro) may facilitate searching for new therapies for SARS-COV-2. The aim was to assess the effectiveness of available FDA approved drugs which can construct a covalent bond with Cys145 inside binding site SARS-CoV-2 main protease by using covalent docking screening. We conducted the covdock module MMGBSA module in the Schrodinger suite 2020-1, to examine the covalent bonding utilizing. Besides, we submitted the top three drugs to molecular dynamics simulations via Gromacs 2018.1. The covalent docking showed that saquinavir, ritonavir, remdesivir, delavirdine, cefuroxime axetil, oseltamivir and prevacid have the highest binding energies MMGBSA of –72.17, −72.02, −65.19, −57.65, −54.25, −51.8, and −51.14 kcal/mol, respectively. The 50 ns molecular dynamics simulation was conducted for saquinavir, ritonavir and remdesivir to evaluate the stability of these drugs inside the binding pocket of SARS-CoV-2 main protease. The current study provides a powerful in silico results, means for rapid screening of drugs as anti-protease medications and recommend that the above-mentioned drugs can be used in the treatment of SARS-CoV-2 in combined or sole therapy.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• covalent docking
• drug repurposing
• MD simulation
• PCA
• Mpro

Acknowledgements

Authors thankful for staff membered of Gaziantep University Institute of Health Sciences, Department of Bioinformatics and Computational Biology.

Disclosure statement

The authors declare no conflict of interest.