In Silico Screening for Natural Ligands to Non-Structural Nsp7 Conformers of Coronaviruses

17 September 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The non-structural protein 7 (nsp7) of Severe Acute Respiratory Syndrome (SARS) coronaviruses was selected as a new target to potentially interfere with viral replication. The nsp7s are one of the most conserved, unique and small coronavirus proteins having a critical, yet intriguing participation on the replication of the long viral RNA genome after complexing with nsp8 and nsp12. Despite the difficulties of having no previous binding pocket, two high-throughput virtual blind screening of 158240 natural compounds > 400 Da by AutoDock Vina against nsp7.1ysy identified 655 leads displaying predicted binding affinities between 10 to 1100 nM. The leads were then screened against 14 available conformations of nsp7 by both AutoDock Vina and seeSAR programs employing different binding score algorithms, to identify 20 consensus top-leads. Further in silico predictive analysis of physiological and toxicity ADMET criteria (chemical properties, adsorption, metabolism, toxicity) narrowed top-leads to a few drug-like ligands many of them showing steroid-like structures. A final optimization by search for structural similarity to the top drug-like ligand that were also commercially available, yielded a collection of predicted novel ligands with ~100-fold higher-affinity whose antiviral activity may be experimentally validated. Additionally, these novel nsp7-interacting ligands and/or their further optimized derivatives, may offer new tools to investigate the intriguing role of nsp7 on replication of coronaviruses.

Keywords

nsp7
conformers
coronavirus
virtual screening
ligands
steroid-like scaffolds
SARS CoV-19

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