Identification of new anti-nCoV drug chemical compounds from Indian spices exploiting SARS-CoV-2 main protease as target

Abstract

The 2019-novel coronavirus (nCoV) has caused a global health crisis by causing coronavirus disease-19 (COVID-19) pandemic in the human population. The unavailability of specific vaccines and anti-viral drug for nCoV, science demands sincere efforts in the field of drug design and discovery for COVID-19. The novel coronavirus main protease (SARS-CoV-2 Mpro) play a crucial role during the disease propagation, and hence SARS-CoV-2 Mpro represents as a drug target for the drug discovery. Herein, we have applied bioinformatics approach for screening of chemical compounds from Indian spices as potent inhibitors of SARS-CoV-2 main protease (PDBID: 6Y84). The structure files of Indian spices chemical compounds were taken from PubChem database or Zinc database and screened by molecular docking, by using AutoDock-4.2, MGLTools-1.5.6, Raccoon virtual screening tools. Top 04 hits based on their highest binding affinity were analyzed. Carnosol exhibited highest binding affinity -8.2 Kcal/mol and strong and stable interactions with the amino acid residues present on the active site of SARS-CoV-2 Mpro. Arjunglucoside-I (-7.88 Kcal/mol) and Rosmanol (-7.99 Kcal/mol) also showed a strong and stable binding affinity with favourable ADME properties. These compounds on MD simulations for 50 ns shows strong hydrogen-bonding interactions with the protein active site and remains stable inside the active site. Our virtual screening results suggest that these small chemical molecules can be used as potential inhibitors against SARS-CoV-2 Mpro and may have an anti-viral effect on nCoV. However, further validation and investigation of these inhibitors against SARS-CoV-2 main protease are needed to claim their candidacy for clinical trials.

Communicated by Ramaswamy H. Sarma

Keywords:

• Novel coronavirus (nCoV)
• corona virus disease-2019 (COVID-19)
• novel coronavirus main protease (SARS-CoV-2 Mpro)
• molecular docking
• bioinformatics
• ADME

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The infrastructure facilities by IIT (BHU) Varanasi is acknowledged. Umesh is supported by CSIR project [27(344)/19-EMR-II] to VKD. DK acknowledges research fellowship from IIT (BHU) Varanasi. VKD also acknowledges SERB funding [CVD/2020/000031]. The Authors CS and SKS thankfully acknowledge RUSA-Phase 2.0 Policy (TNmulti-Gen), Dept. of Edn, Govt. of India (Grant No: F.24-51/2014-U).