A comprehensive review on promising anti-viral therapeutic candidates identified against main protease from SARS-CoV-2 through various computational methods

• Main Authors: Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh, Jayaraman Muthukumaran, Amit Kumar Singh
• Format: Article
• Language: English
• Published: SpringerOpen 2020-11-01
• Series: Journal of Genetic Engineering and Biotechnology
• Subjects: 3CLpro; In silico; Inhibitors; Structure-based virtual screening (SBVS); Ligand-based virtual screening (LBVS); Drug-repurposing
• Online Access: http://link.springer.com/article/10.1186/s43141-020-00085-z

Abstract Background The COVID-19 pandemic caused by SARS-CoV-2 has shown an exponential trend of infected people across the planet. Crediting its virulent nature, it becomes imperative to identify potential therapeutic agents against the deadly virus. The 3-chymotrypsin-like protease (3CLpro) is a cysteine protease which causes the proteolysis of the replicase polyproteins to generate functional proteins, which is a crucial step for viral replication and infection. Computational methods have been applied in recent studies to identify promising inhibitors against 3CLpro to inhibit the viral activity. Main body of the abstract This review provides an overview of promising drug/lead candidates identified so far against 3CLpro through various in silico approaches such as structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS) and drug-repurposing/drug-reprofiling/drug-retasking. Further, the drugs have been classified according to their chemical structures or biological activity into flavonoids, peptides, terpenes, quinolines, nucleoside and nucleotide analogues, protease inhibitors, phenalene and antibiotic derivatives. These are then individually discussed based on the various structural parameters namely estimated free energy of binding (ΔG), key interacting residues, types of intermolecular interactions and structural stability of 3CLpro-ligand complexes obtained from the results of molecular dynamics (MD) simulations. Conclusion The review provides comprehensive information of potential inhibitors identified through several computational methods thus far against 3CLpro from SARS-CoV-2 and provides a better understanding of their interaction patterns and dynamic states of free and ligand-bound 3CLpro structures.