Identification of potential anti-TMPRSS2 natural products through homology modelling, virtual screening and molecular dynamics simulation studies

Abstract

Recent outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to a pandemic of COVID-19. The absence of a therapeutic drug and vaccine is causing severe loss of life and economy worldwide. SARS-CoV and SARS-CoV-2 employ the host cellular serine protease TMPRSS2 for spike (S) protein priming for viral entry into host cells. A potential way to reduce the initial site of SARS-CoV-2 infection may be to inhibit the activity of TMPRSS2. In the current study, the three-dimensional structure of TMPRSS2 was generated by homology modelling and subsequently validated with a number of parameters. The structure-based virtual screening of Selleckchem database was performed through ‘Virtual Work Flow’ (VSW) to find out potential lead-like TMPRSS2 inhibitors. Camostat and bromhexine are known TMPRSS2 inhibitor drugs, hence these were used as control molecules throughout the study. Based on better dock score, binding-free energy and binding interactions compared to the control molecules, six molecules (Neohesperidin, Myricitrin, Quercitrin, Naringin, Icariin, and Ambroxol) were found to be promising against the TMPRSS2. Binding interactions analysis revealed a number of significant binding interactions with binding site amino residues of TMPRSS2. The all-atoms molecular dynamics (MD) simulation study indicated that all proposed molecules retain inside the receptor in dynamic states. The binding energy calculated from the MD simulation trajectories also favour the strong affinity of the molecules towards the TMPRSS2. Proposed molecules belong to the bioflavonoid class of phytochemicals and are reported to possess antiviral activity, our study indicates their possible potential for application in COVID-19.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• COVID-19
• TMPRSS2
• natural products
• virtual screening
• molecular docking
• molecular dynamics

Disclosure statement

The authors declare that there is no competing interest.

Computational resources

The CHPC (www.chpc.ac.za), Cape Town, South Africa is thankfully acknowledged for computational resources and tools.

Additional information

Funding

The authors are grateful to the Researchers Supporting Project No. (RSP-2020/161), King Saud University, Riyadh, Saudi Arabia.