A computational approach for the screening of potential antiviral compounds against SARS-CoV-2 protease: Ionic liquid vs herbal and natural compounds

Saraswat, Juhi; Singh, Prashant; Patel, Rajan

The current scenario across the globe shows unprecedented healthcare and an economic crisis due to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Recently, the World Health Organization (WHO) has declared a pandemic stage worldwide because of the high mortality and morbidity rate caused by novel infection disease. There have been several clinical trials and identification underway to find a treatment of this novel virus. For the treatment of severe infection involves the blocking of the replication of its CoV-2 protein. Hydroxychloroquine and remdesivir has been used on an emergency basis for its treatment. The uncontrolled infection and increasing death rate underline the emergence to develop the antiviral drug. In our study, the blind docking of various classes of compounds including control antiviral drugs (abacavir, acyclovir, quinoline, hydroxyquinoline), antimicrobial drugs (levofloxacin, amoxicillin, cloxacin, ofloxacin), natural compounds (lycorine, saikosaponins, myricetin, amentaflavone), herbal compounds (silymarin, palmatine, curcumin, eugenin) available in Indian Ayurveda was done. Besides, we have also performed the blind docking of various ionic liquids (ILs) such as pyrrolidinium, piperidinium, pyridinium, imidazolium based ILs against CoV-2 protease as they have recently emerged as a potential antimicrobial agent. Further, the pharmacokinetic properties and cytotoxicity of the compounds were determined computationally. The docking results showed successful binding to the active site or near a crucial site. The present computational approach was found helpful to predict the best possible inhibitor of protease and may result in an effective therapeutic agent against COVID-19.