In Silico Exploration of Potential Natural Inhibitors against SARS-Cov-2 nsp10

Abstract

In continuation of our previous effort, different <i>in silico</i> selection methods were applied to 310 naturally isolated metabolites that exhibited antiviral potentialities before. The applied selection methods aimed to pick the most relevant inhibitor of SARS-CoV-2 nsp10. At first, a structural similarity study against the co-crystallized ligand, S-Adenosyl Methionine (<b>SAM</b>), of SARS-CoV-2 nonstructural protein (nsp10) (PDB ID: 6W4H) was carried out. The similarity analysis culled 30 candidates. Secondly, a fingerprint study against <b>SAM</b> preferred compounds <b>44</b>, <b>48</b>, <b>85</b>, <b>102</b>, <b>105</b>, <b>182</b>, <b>220</b>, <b>221</b>, <b>282</b>, <b>284</b>, <b>285</b>, <b>301</b>, and <b>302</b>. The docking studies picked <b>48</b>, <b>182</b>, <b>220</b>, <b>221</b>, and <b>284</b>. While the ADMET analysis expected the likeness of the five candidates to be drugs, the toxicity study preferred compounds <b>48</b> and <b>182</b>. Finally, a density-functional theory (DFT) study suggested vidarabine (<b>182</b>) to be the most relevant SARS-Cov-2 nsp10 inhibitor.