Computational screening of natural products to identify potential inhibitors for human neuropilin-1 (NRP1) receptor to abrogate the binding of SARS-CoV-2 and host cell

Abstract

Recently, a new variant B.1.1.529 or Omicron variant and its sub-variants (BA2.75, BA.5) of SARS-CoV-2 (Severe acute respiratory virus 2) have been reported with a larger number of mutations in the spike protein and particularly in the RBD (receptor-binding domain). The omicron (B.1.1.529) variant has aggravated the pandemic situation further and needs more analysis for therapeutic development. Keeping in view the urgency of the required data, the current study used molecular modeling and simulation-based methods to target the NRP1 (Neuropilin 1) protein to halt the entry into the host cell. Employing a molecular screening approach to screen the North-East African natural compounds database (NEANCDB) revealed Subereamine B with a docking score of −8.44 kcal/mol, Zinolol with the docking score of −8.05 while Subereamine A with a docking score of −7.88 kcal/mol as the best hits against NRP1. Molecular simulation-based further validation revealed stable dynamics, good structural packing, and dynamic residues flexibility index. Moreover, hydrogen bonding fraction analysis demonstrated the interactions remained sustained during the simulation. Furthermore, the total binding free energy for Subereamine B was −44.24 ±0.91 kcal/mol, for Zinolol −34.32 ±0.40 kcal/mol while for Subereamine A the TBE was calculated to be −41.78 ± 0.36 kcal/mol respectively. This shows that the two arginine-based alkaloids, i.e. Subereamine B and Subereamine A could inhibit the NRP1 more strongly than Zinolol. In conclusion, this study provides a basis for the development of novel drugs against SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19
• Omicron
• B.1.1.529
• structural modeling
• MD Simulations

Acknowledgments

The researchers would like to thank University of Jeddah, Jeddah 21959, Saudi Arabia for funding the publication of this project.

Disclosure statement

The author declares no conflict of interest.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Author contributions

Conceptualization: Alaa Karkashan; Data curation, Alaa Karkashan and Roba Attar. Formal analysis: Alaa Karkashan. Funding acquisition: Alaa Karkashan. Investigation: Alaa Karkashan and Roba Attar. Methodology: Alaa Karkashan and Roba Attar. Project administration: Alaa Karkashan. Resources: Alaa Karkashan and Roba Attar. Software: Alaa Karkashan and Roba Attar. Supervision: Alaa Karkashan. Validation: Roba Attar. Visualization: Alaa Karkashan. Writing—original draft: Alaa Karkashan. Writing—review & editing: Roba Attar.

Data availability statement

The data presented in this study are available within the article.