Structure-Based Identification of SARS-CoV-2 nsp10-16 Methyltransferase Inhibitors Using Molecular Dynamics Insights.

Abstract

SARS-CoV-2 evades immune detection via nsp10-16 methyltransferase-mediated 2'-O-methylation of viral mRNA, making it a key antiviral target. Our study employed structure-based drug discovery-including virtual screening, molecular docking, and molecular dynamics (MD) simulations-to identify potent inhibitors of nsp10-16. We identified seven promising inhibitors (Z1-Z7) targeting the binding site of the SARS-CoV-2 nsp10-16 methyltransferase, with Z2, Z3, Z4, and Z7 exhibiting strong binding affinities. Further, molecular dynamics simulations confirmed that Z2, Z3, and Z7 effectively stabilized the enzyme by reducing conformational fluctuations and maintaining structural compactness, comparable to the native ligand-bound complex. The conformational deviation revealed that Z2, Z6, and Z7 restricted large-scale conformational transitions, reinforcing their stabilizing effect on the enzyme. The binding free energy calculations ranked Z4 (-37.26 kcal/mol), Z7 (-35.37 kcal/mol), and Z6 (-35.22 kcal/mol) as the strongest binders, surpassing the native tubercidin complex (-23.70 kcal/mol). The interactions analysis identified Asp99, Tyr132, and Cys115 as key stabilizing residues, with Z2, Z6, and Z7 forming high-lifetime hydrogen bonds. The drug-likeness analysis highlighted the selected compounds as promising candidates, exhibiting high gastrointestinal absorption, optimal solubility, and minimal CYP450 inhibition. Further experimental validation and lead optimization are needed to develop potent methyltransferase inhibitors with improved pharmacokinetics and antiviral efficacy.