In silico investigation of spice molecules as potent inhibitor of SARS-CoV-2

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel infectious disease that is in rapid growth. Several trials are going on worldwide to find a solution for this pandemic. The viral replication can be blocked by inhibiting the receptor-binding domain (RBD) of SARS-CoV-2 spike protein (SARS-CoV-2 RBD Spro) and the SARS-CoV-2 main protease (SARS-CoV-2 Mpro). The binding of potential small molecules to these proteins can inhibit the replication and transcription of the virus. The spice molecules that are used in our food have antiviral, antifungal and antimicrobial properties. As spice molecules are consumed in the diet, hence its antiviral properties against SARS-CoV-2 will benefit in a significant manner. Therefore, in this work, the molecular docking of 30 selected spice molecules (screened through ADME property) was performed to identify the potential inhibitors for the RBD Spro and Mpro of SARS-CoV-2. We have found that though all the molecules bind actively with the SARS-CoV-2 RBD Spro and Mpro, but Piperine has the highest binding affinity among the 30 screened molecules. Besides, the comparative study between Piperine and currently used drugs show that Piperine is more effective. The interaction of Piperine with RBD Spro and Mpro is further validated by the molecular dynamics (MD) simulation studies. The free energy landscape and binding free energy results also, support for the stable complex formation of Piperine with RBD Spro and Mpro. We anticipate immediate wet-lab experiments and clinical trials in support of this computational study that might help to inhibit the SARS-CoV-2 virus.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• SARS-CoV-2
• COVID-19
• receptor-binding domain
• spike proteins
• main protease
• spice molecules
• inhibition

Acknowledgements

The authors are thankful to the Ministry of Human Resource Development (MHRD), New Delhi, for financial assistance (MHRD/(FDC)/2015–2016/438/INST) to establish the computational facility. We are also extremely grateful to Dr. Anand Kant Das, New York University, Abu Dhabi, for a fruitful scientific discussion.

Disclosure statement

The authors declare no conflict of interest.