Antiviral nanoparticle ligands identified with datamining and high-throughput virtual screening?

RSC Advances Pub Date: 2021-07-01 DOI: 10.1039/D1RA02293H

Abstract

To help contain the spread of the COVID-19 pandemic and to protect front-line workers, new antiviral measures are required. Antiviral nanoparticles are one such possible measure. Metal nanoparticles made from a variety of metals including gold, silver, and copper can kill or disable viruses that cause significant health problems in humans (such as SARS-CoV-2, HIV, or influenza). To promote interaction between nanoparticles and viruses the stabilizing ligands on the nanoparticle surface should be optimized for docking with proteins. The enormous chemical space of possible nanoparticle ligands makes this optimization experimentally and computationally intractable. Here we present a datamining-based study that searched for nanoparticle ligands that have previously been used, and computationally tested these for their ability to dock with the SARS-CoV-2 spike glycoprotein. These ligands will coat future antiviral nanoparticles to be used outside of the body, not as drugs. The best of these ligands identified were: nitric acid (score: 0.95), phosphoroselenoic acid (score: 0.88), hydroxyammonium (score: 0.83), pyrophosphoric acid (score: 0.81). Inspection of the best of these ligands has suggested design principles for future antiviral nanoparticle ligands, and we suggest further ligands based on these principles. These results will be used to inspire further in vitro and in silico experimentation to accelerate the development of antiviral nanoparticles.

Graphical abstract: Antiviral nanoparticle ligands identified with datamining and high-throughput virtual screening
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