Marine algal antagonists targeting 3CL protease and spike glycoprotein of SARS-CoV-2: a computational approach for anti-COVID-19 drug discovery

Abstract

The COVID-19 pandemic has severely destructed human life worldwide, with no suitable treatment until now. SARS-CoV-2 virus is unprecedented, resistance against number of therapeutics and spreading rapidly with high mortality, which warrants the need to discover new effective drugs to combat this situation. This current study is undertaken to explore the antiviral potential of marine algal compounds to inhibit the viral entry and its multiplication using computational analysis. Among the proven drug discovery targets of SARS-CoV-2, spike glycoprotein and 3-chymotrypsin-like protease are responsible for the virus attachment and viral genome replication in the host cell. In this study, the above-mentioned drug targets were docked with marine algal compounds (sulfated polysaccharides, polysaccharide derivatives and polyphenols) using molecular docking tools (AutoDockTools). The obtained results indicate that κ-carrageenan, laminarin, eckol, trifucol and β-D-galactose are the top-ranking compounds showing better docking scores with SARS-CoV-2 targets, than the current experimental COVID-19 antiviral drugs like dexamethasone, remdesivir, favipiravir and MIV-150. Further, molecular dynamic simulation, ADMET and density functional theory calculations were evaluated to substantiate the findings. To the best of our knowledge, this is the first report on in silico analysis of aforesaid algal metabolites against SARS-CoV-2 targets. This study concludes that these metabolites can be curative for COVID-19 in the hour of need after further validations in in vitro and in vivo testings.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19
• SARS-CoV-2
• molecular docking
• antiviral drugs
• 3CL protease & spike glycoprotein

Acknowledgements

The authors thank the Department of Biotechnology (DBT), New Delhi, India for the financial support, DST-FIST, DST-PURSE, University Grant Commission (UGC)-SAP, UGC-UPE program of MKU for the infrastructure, instrumentation facility and International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi for Molecular dynamic simulation and ADMET studies using Schrodinger software.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

The authors thank the Department of Biotechnology (DBT), New Delhi, India (No: BT/PR15677/AAQ/3/799/2016), for the financial support to PV.