Targeting SARS-CoV-2: a systematic drug repurposing approach to identify promising inhibitors against 3C-like proteinase and 2′-O-ribose methyltransferase

Abstract

The recent pandemic associated with SARS-CoV-2, a virus of the Coronaviridae family, has resulted in an unprecedented number of infected people. The highly contagious nature of this virus makes it imperative for us to identify promising inhibitors from pre-existing antiviral drugs. Two druggable targets, namely 3C-like proteinase (3CLpro) and 2′-O-ribose methyltransferase (2′-O-MTase) were selected in this study due to their indispensable nature in the viral life cycle. 3CLpro is a cysteine protease responsible for the proteolysis of replicase polyproteins resulting in the formation of various functional proteins, whereas 2′-O-MTase methylates the ribose 2′-O position of the first and second nucleotide of viral mRNA, which sequesters it from the host immune system. The selected drug target proteins were screened against an in-house library of 123 antiviral drugs. Two promising drug molecules were identified for each protein based on their estimated free energy of binding (ΔG), the orientation of drug molecules in the active site and the interacting residues. The selected protein-drug complexes were then subjected to MD simulation, which consists of various structural parameters to equivalently reflect their physiological state. From the virtual screening results, two drug molecules were selected for each drug target protein [Paritaprevir (ΔG = −9.8 kcal/mol) & Raltegravir (ΔG = −7.8 kcal/mol) for 3CLpro and Dolutegravir (ΔG = −9.4 kcal/mol) and Bictegravir (ΔG = −8.4 kcal/mol) for 2′-OMTase]. After the extensive computational analysis, we proposed that Raltegravir, Paritaprevir, Bictegravir and Dolutegravir are excellent lead candidates for these crucial proteins and they could become potential therapeutic drugs against SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Keywords:

• Drug repurposing
• SARS-CoV-2
• 3C-like proteinase
• 2′-O-ribose methyltransferase
• docking
• MD simulation

Acknowledgements

Dr. Amit Kumar Singh thanks the Department of Science and Technology (DST) and Indian National Science Academy (INSA), New Delhi, India. Gizachew Muluneh Amera thanks the College of Natural Science, Wollo University, Dessie, Ethiopia for the sponsorship. The authors also thank to Supercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical standards

Ethical standards are compulsory for studies relating to human and animal subjects.