Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2

Abstract

COVID-19 (Corona Virus Disease of 2019) caused by the novel ‘Severe Acute Respiratory Syndrome Coronavirus-2’ (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. ‘Non-structural protein 15’ (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski’s rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Keywords:

• Covid-19
• Nsp15
• structure-based pharmacophore designing and virtual screening
• antivirals
• MD simulation
• and MM-PBSA

Disclosure statement

There are no conflicts of interest declared by the authors.

Author’s contribution

Design of Study: Prakash Jha, Madhu Chopra, and Daman Saluja, Methodology, and Implementation of Software: Prakash Jha, Analysis of result: Prakash Jha and Madhu Chopra, Writing, and editing of original manuscript: Prakash Jha and Madhu Chopra, Reviewing the manuscript: Madhu Chopra, and Daman Saluja, Funding Support: Madhu Chopra, and Daman Saluja.

Data availability statement

The datasets supporting the results and conclusion of this manuscript are included within the article and its supplementary information files.

Additional information

Funding

Authors thankfully acknowledge the Bioinformatics Centre (BIC), Department of Biotechnology, Govt. of India (grant # BT/PR40153/BTIS/137/8/2021 to MC & DS) and Institution of Eminence, University of Delhi for financial support (#IoE/FRP/LS/2020/27 to MC). The authors acknowledge the ACBR, University of Delhi for lending bioinformatics infrastructural facility (BIC) and Bioinformatics Resources and Applications Facility (BRAF), C-DAC, ‘Pune’ for providing server assistance. PJ was recipient of a PhD fellowship from DST-Inspire by grant number (DST/INSPIRE/03/2016/000026).